WO2019196224A1 - Regulation information processing method and apparatus, computer device and storage medium - Google Patents

Regulation information processing method and apparatus, computer device and storage medium Download PDF

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Publication number
WO2019196224A1
WO2019196224A1 PCT/CN2018/095424 CN2018095424W WO2019196224A1 WO 2019196224 A1 WO2019196224 A1 WO 2019196224A1 CN 2018095424 W CN2018095424 W CN 2018095424W WO 2019196224 A1 WO2019196224 A1 WO 2019196224A1
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WO
WIPO (PCT)
Prior art keywords
information
file
terminal
learning
target
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PCT/CN2018/095424
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French (fr)
Chinese (zh)
Inventor
韩梅
张安元
邓华威
王科
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平安科技（深圳）有限公司
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Publication of WO2019196224A1 publication Critical patent/WO2019196224A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/10—Office automation; Time management
    • G06Q10/103—Workflow collaboration or project management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/10—Office automation; Time management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/31—Indexing; Data structures therefor; Storage structures
    • G06F16/316—Indexing structures
    • G06F16/322—Trees
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/10—Office automation; Time management
    • G06Q10/109—Time management, e.g. calendars, reminders, meetings or time accounting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/20—Education
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/20—Education
    • G06Q50/205—Education administration or guidance
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B7/00—Electrically-operated teaching apparatus or devices working with questions and answers

Definitions

  • the present application relates to a system information processing method, apparatus, computer device and storage medium.
  • Institutional norms are the rules and guidelines that employees must abide by in their production and operation activities, including laws and policies, organizational structure, management systems, job responsibilities, technical standards, and work processes.
  • institutions For the published system, enterprises need to continuously carry out system publicity and urge employees to carry out institutional learning, so as to ensure that the system can play a guiding role in actual business activities.
  • the inventor realized that this method requires a large amount of working time, which increases the system promotion cost and the system learning cost.
  • a system information processing method, apparatus, computer device, and storage medium are provided.
  • An institutional information processing method includes: receiving an institutional learning request sent by a first terminal, where the system learning request carries an applicable object identifier and a query condition; and acquiring an associated information tree corresponding to the applicable object identifier; the associated information tree includes a plurality of information nodes and a plurality of system sub-files associated with each of the information nodes; searching for an information node that satisfies the query condition in the association information tree; and acquiring a system sub-file corresponding to the found information node, The system sub-file is split into a plurality of file segments, and the plurality of the file segments are pushed to the first terminal; the learning event of the file segment generated by the first terminal is captured, and the learning event is acquired. Institutional learning data; the institutional learning data includes an effective learning time; and when the effective learning time reaches a threshold, acquiring a target resource, and transferring the target resource to the first terminal.
  • An system information processing apparatus includes: an system query module, configured to receive an institutional learning request sent by a first terminal, where the system learning request carries an applicable object identifier and a query condition; and acquires an associated information tree corresponding to the applicable object identifier;
  • the association information tree includes a plurality of information nodes and a plurality of system sub-files associated with each of the information nodes; searching, in the association information tree, an information node that satisfies the query condition; and an system splitting module for acquiring a system sub-file corresponding to the found information node, splitting the system sub-file into a plurality of file segments, and pushing a plurality of the file segments to the first terminal; and a learning monitoring module, configured to capture the a learning event for the file segment generated by a terminal, acquiring institutional learning data corresponding to the learning event; the institutional learning data includes an effective learning time; and when the effective learning time reaches a threshold, acquiring a target resource, The target resource is transferred to the first terminal.
  • a computer apparatus comprising a memory and one or more processors having stored therein computer readable instructions that, when executed by a processor, implement the steps of the system information processing method provided in any one of the embodiments of the present application.
  • One or more non-volatile storage media storing computer readable instructions, when executed by one or more processors, causing one or more processors to implement a system as provided in any one embodiment of the present application The steps of the information processing method.
  • FIG. 1 is an application scenario diagram of a system information processing method according to one or more embodiments
  • FIG. 2 is a flow diagram of a method of processing institutional information in accordance with one or more embodiments.
  • FIG. 3 is a flow diagram of the steps of constructing an associated information tree in accordance with one or more embodiments.
  • FIG. 4 is a schematic diagram of a target information tree in a system information processing method in accordance with one or more embodiments.
  • FIG. 5 is a schematic diagram of an associated information tree in a system information processing method in accordance with one or more embodiments.
  • FIG. 6 is a block diagram showing the structure of an institutional information processing apparatus according to one or more embodiments.
  • FIG. 7 is a block diagram of a computer device in accordance with one or more embodiments.
  • the system information processing method provided by the present application can be applied to an application environment as shown in FIG. 1.
  • the first terminal 102 communicates with the server 104 over a network.
  • the second terminal 106 communicates with the server 104 over a network.
  • the first terminal 102 and the second terminal 106 can be, but are not limited to, various personal computers, notebook computers, smart phones, tablets, and portable wearable devices.
  • the first terminal 102 is a service terminal, and the user can perform operations such as system learning at the first terminal 102.
  • the second terminal 106 is a system management terminal, and the user can perform system drafting, opinion collection, approval, and release in the second terminal 106.
  • the first terminal 102 and the second terminal 106 may be the same terminal or different terminals.
  • the server 104 can be implemented by a stand-alone server or a server cluster composed of a plurality of servers.
  • an institutional learning request is sent to the server 104.
  • the institutional learning request carries the applicable object identification and query conditions.
  • the server 104 acquires an association information tree corresponding to the applicable object identifier.
  • the association information tree includes a plurality of information nodes and a system sub-file associated with each information node.
  • the server 104 looks in the association information tree whether there is an information node that satisfies the query condition. If so, the server 104 acquires a system subfile associated with the information node that satisfies the query condition, splits the system subfile into a plurality of file segments, and pushes the plurality of file segments to the first terminal 102.
  • the user can perform institutional learning at the first terminal 102.
  • the first terminal 102 has previously set a buried point.
  • the first terminal 102 intercepts the learning event corresponding to the touch operation and reports the learning event to the server 104.
  • the server 104 captures the learning event of the system sub-file generated by the first terminal, and acquires the system learning data corresponding to the learning event.
  • Institutional learning data includes user identification and corresponding effective learning time.
  • the server determines whether the effective learning time reaches the threshold. If yes, the target resource is acquired, and the target resource is transferred to the first terminal 102.
  • the system sub-file is divided into a plurality of file fragments with small data volume, so that the user can use the fragmentation time for system learning; when the effective learning time reaches the threshold, the target resource is rewarded, and the user is promoted to system learning. Enthusiasm, automatically monitor the user's institutional learning, reduce system promotion costs and learning costs.
  • a system information processing method is provided.
  • the method is applied to the server in FIG. 1 as an example, and includes the following steps:
  • Step 202 Receive an institutional learning request sent by the first terminal, where the system learning request carries the applicable object identifier and the query condition.
  • the association information tree includes a plurality of information nodes and a system sub-file associated with each information node.
  • the server classifies and splits the system information, and adds the split system information to the corresponding associated information tree.
  • the server pushes the associated information tree to the first terminal corresponding to the corresponding post, so that the corresponding post user can refer to the query for learning.
  • the user can conduct system query learning through the business system at the business terminal.
  • the first terminal triggers the system query request according to the query operation of the user on the associated information tree. Send an institutional query request to the server.
  • the system query request includes a first query request and a second query request. For example, when the second terminal detects that the mouse stays at a certain information node exceeds a threshold, the second terminal sends a first query request to the server. When the second terminal detects a mouse click operation of the mouse on an information node, the second terminal sends a second query request to the server.
  • the first query request carries the user identification and query conditions.
  • the query condition can be one or more keywords.
  • Step 204 Acquire an association information tree corresponding to the applicable object identifier.
  • the association information tree includes multiple information nodes and multiple system sub-files associated with each information node.
  • Step 206 Find an information node that satisfies the query condition in the association information tree.
  • the server obtains the applicable object identifier corresponding to the user identifier according to the first query request.
  • the user identifier is used to locate the operation object of the query operation event, and may be at least one of a login account of the service system or an IP address (Internet Protocol Address) of the service terminal.
  • Each information node in the associated information tree is associated with a corresponding information digest.
  • the information summary records the purpose of the corresponding system information, the main content introduction or the scope of application.
  • the information node or its associated information digest contains multiple keywords in the query condition, it indicates that the information node satisfies the query condition.
  • the server When there is an information node that satisfies the query condition, the server obtains the information digest associated with the information node, and returns the information digest to the first terminal.
  • the message summary can be generated based on the system description information.
  • the first terminal popup window displays a summary of information corresponding to the directory node, so that the user determines whether the information node is the system information that needs to be searched for. If yes, the corresponding item detailed information is further obtained from the second query request to reduce unnecessary data transmission between the first terminal and the server.
  • the item details may be the system sub-file corresponding to the clicked information node.
  • Step 208 Acquire a system sub-file corresponding to the found information node, split the system sub-file into a plurality of file segments, and push the plurality of file segments to the first terminal.
  • the server calculates the amount of data in the system subfile and detects whether the data amount exceeds the threshold.
  • the threshold may be preset or may be temporarily generated based on the load monitoring result of the server.
  • the server splits the queried system sub-file into a plurality of file segments with small data volume, and pushes multiple file segments to the first terminal.
  • splitting the system sub-file into a plurality of file segments, and pushing the plurality of file segments to the first terminal comprises: acquiring a file type of the system sub-file; and obtaining a corresponding data amount threshold according to the file type; The system sub-file is split according to the data volume threshold to obtain a plurality of file segments; according to the splitting sequence, the plurality of file segments are sequentially pushed to the first terminal.
  • the system subfile can be multiple types of files, such as doc documents, pdf documents, xls tables, mp3 audio or avi videos.
  • Different file types can have different data volume thresholds.
  • the data volume threshold may be temporarily generated according to the system learning request triggered by the user, or may be temporarily generated according to the load monitoring result of other servers in the plurality of clusters, or may be preset.
  • the splitting methods corresponding to different types of system sub-files can be different. For example, when the system sub-file is video or audio, the corresponding split mode may be split using a preset split interface.
  • the default split interface can be OLEDB (an application program interface) and the like.
  • the server traverses the system sub-file line by line, and matches the split expression corresponding to each applicable object identifier with multiple system terms in the system file, respectively, and The system clauses that match the successful expression of the split expression are split into a corresponding system sub-file corresponding to the applicable object identifier, thereby obtaining the system sub-file of the system file in multiple split dimensions.
  • the server determines the split location of the system subfile based on the data volume threshold. For example, the data volume of the system sub-file A is 720M. If the data volume threshold is 80M, the 80M size position of the system sub-file is marked as the first split position, and the 160M-size position is marked as the second split. Sub-position, and so on. The server identifies if each split location is between adjacent separators. When the split location is located at a location where the separator is located, the server splits the system subfile at the split location to obtain multiple file fragments corresponding to the system subfile.
  • the server splits the corresponding system subfile at any one of the adjacent separators, that is, the previous separator or the latter one of the adjacent separators
  • the separator is split to obtain multiple file fragments corresponding to the system subfile.
  • the server sends multiple file fragments to the first terminal in the split order.
  • Step 210 Capture a learning event of a file segment that occurs at the first terminal, and acquire system learning data corresponding to the learning event; the system learning data includes an effective learning time.
  • the first terminal is pre-set with a buried point.
  • the first terminal displays an institutional learning interface.
  • the institutional learning interface includes multiple controls. Controls include buttons, windows, text boxes, scroll bars, and more. Many of the controls are pre-populated (hereinafter referred to as "buried point controls").
  • buried point controls When the user performs a touch operation on the embedded control in the system learning interface, the first terminal intercepts the learning event corresponding to the touch operation, and reports the learning event to the server.
  • the server captures a learning event of the file segment that occurs at the first terminal, and acquires system learning data corresponding to the learning event.
  • the institutional learning data includes basic data such as one or more file segment identifiers and learning time corresponding to each file segment identifier.
  • the institutional learning data also includes the effective learning time corresponding to the user identification. The effective learning time can be calculated from the basic data.
  • Step 212 When the effective learning time reaches the threshold, the target resource is acquired, and the target resource is transferred to the first terminal.
  • the server monitors the effective learning time of the user during the monitoring period.
  • the monitoring period can be set freely according to actual needs, such as the legal working hours from 8:00 am to 9:00 pm.
  • the server determines whether the effective learning time of the user reaches the threshold.
  • the server acquires the target resource, transfers the target resource to the first terminal, and rewards the user with the resource.
  • the target resource may be a fund resource or a privilege resource, and the like.
  • the server may increase the system query authority corresponding to the corresponding user identifier or other operation authority to the business system according to the effective learning time.
  • the server may obtain a corresponding share of the fund resource according to the effective learning time, and perform value transfer on the first terminal according to the obtained fund resource.
  • the capital resources may be vouchers resources, red packets resources, and the like. It is easy to understand that the share of capital resources can adapt to changes with the length of effective learning, or it can be a random share, or it can be a fixed quota, which is not limited.
  • acquiring the target resource, and transferring the target resource to the first terminal includes: sending the resource extraction page to the first terminal when the effective learning time reaches the threshold; monitoring the first terminal The resource extraction operation that occurs on the resource extraction page acquires the target resource of the random share according to the resource extraction operation; and transfers the acquired target resource to the first terminal.
  • the server sends a resource extraction page to the first terminal.
  • the resource extraction page includes a resource extraction button and a plurality of resource options.
  • the server monitors the resource extraction operation that occurs on the resource extraction page of the first terminal.
  • the resource extraction operation may be a touch operation on the resource extraction button.
  • the server randomly acquires one resource as a target resource among the multiple resource options; and transfers the acquired target resource to the first terminal.
  • the resource extraction page can be a lottery page.
  • the first terminal generates an institutional learning request by using the applicable object identifier and the query condition, and may learn the request according to the associated information tree response system corresponding to the applicable object identifier; in the obtained related information tree, the first query may satisfy the query condition.
  • Information node and associated system sub-file ; splitting the system sub-file into multiple file segments and pushing it to the first terminal, so that the first terminal can perform system learning based on the file segment; learning the system sub-file generated by the first terminal
  • the event is captured, and the system learning data corresponding to the learning event can be obtained; according to whether the effective learning time in the system learning data reaches the threshold, the target resource transfer can be selected.
  • the splitting of the system sub-file into multiple file segments is pushed to the first terminal, it is convenient for the system learning by using the fragmentation time at the first terminal, thereby reducing the system learning cost; automatically monitoring the user's system learning situation, and effectively When the learning time reaches the threshold, the target resources are rewarded, the enthusiasm of the system for learning is improved, and the system promotion cost and learning cost are reduced.
  • the step of constructing the association information tree before the association information tree corresponding to the applicable object identifier is acquired, the step of constructing the association information tree is further included, and the step of constructing the association information tree includes:
  • Step 302 Monitor system information issued by the second terminal; the system information includes system description information and associated system files; the system file includes multiple system terms and applicable object identifiers corresponding to each system clause.
  • Institutional information includes institutional description information and associated institutional documents.
  • the system description information includes the system code, the system name, the system level, the issuing unit, the release date, the applicable object identifier or the information summary.
  • the system information may be text information, voice information, image information, video information, and the like. If it is voice information, image information or video information, voice information, image information and video information can be converted into text information by voice recognition or image processing.
  • the institutional document includes a number of institutional provisions and the applicable object identifier for each system clause. Applicable object identification refers to the identification information of the object that needs to perform or understand the system, and may be a post identification or an organization identification.
  • step 304 the system information is classified, and the system information is added to the preset one or more target information trees according to the classification result.
  • the server classifies the system information. Specifically, the server performs word segmentation on the system information to obtain a corresponding set of original words.
  • the original set of words includes a plurality of original words.
  • the server performs synonymous expansion on each original word to generate a set of extended words corresponding to each original word.
  • the server forms a set of extended system information corresponding to the system information according to each set of extended words, and inputs the set of extended system information into a preset system management model to obtain a target category corresponding to the system information.
  • each target information tree includes a plurality of information nodes and an institutional file associated with each information node.
  • Institutional files can be many types of files, such as pdf documents, jpg images, xls tables, mp3 audio or avi videos.
  • Different information nodes can be arranged in the target information tree according to the release time. It is easy to understand that an institutional information may also have no associated institutional documents, and may also have multiple associated institutional documents, which is not limited.
  • Each target information tree has a corresponding category label.
  • the category label is used to identify the category of the information node that the corresponding target information tree can contain, such as administrative management, sales management, or risk management.
  • the server obtains the category label corresponding to the target category, and filters one or more target information trees including the obtained category label.
  • the server generates an information node based on the system description information. For example, the system number and/or the system name can be used as information nodes.
  • the server associates the system file to the information node, and adds the information node associated with the system file to the target information tree obtained by the screening.
  • Step 306 Acquire multiple association information trees corresponding to the target information tree; each associated information tree has a corresponding applicable object identifier.
  • Each target information tree has a corresponding plurality of associated information trees.
  • Each information node in the target information tree has a corresponding one or more applicable object identifiers.
  • the different applicable object identifiers in the target information tree respectively have a corresponding associated information tree.
  • the number of applicable object identifiers in the target information tree is equal to the number of corresponding association information trees, so that each applicable object identifier corresponding post has a corresponding associated information tree.
  • the target information tree is used to record institutional information that applies to all positions in the enterprise.
  • the associated information tree only needs to record the institutional information applicable to a position.
  • Each associated information tree has a corresponding applicable object identifier.
  • the associated information tree corresponding to the object identifier "post 1" is applied, and the information node 4 and the information are not present in the target information tree of FIG. Node 9. It is easy to understand that the directory hierarchy of multiple information nodes in the associated information tree is not necessarily consistent with the target information tree, and can be adaptively adjusted. The content of the system file record associated with other information nodes still existing in the associated information tree may be different from the content of the system file record associated with the corresponding information node in the target information tree.
  • step 308 the system file is split, and the system sub-file corresponding to the applicable object identifier is generated by using the system clause corresponding to each applicable object identifier.
  • the server splits the multiple system terms in the system file according to the applicable object identifier corresponding to each system clause in the system file, and generates a system sub-file corresponding to each applicable object identifier.
  • the institutional document A includes four system clauses X1 to X4.
  • X1 corresponds to the applicable object identifier including A and B
  • X2 corresponds to the applicable object identifier including A
  • X3 corresponds to the applicable object identifier including A, B, C, D and E
  • X4 corresponds to the applicable object identifier including A and D.
  • Institutional Document A consists of five applicable object identifiers: A, B, C, D and E. The corresponding splits are obtained in five system sub-documents A1 to A5.
  • the system sub-file A1 corresponding to the applicable object identifier A includes four system clauses X1 to X4;
  • the system sub-file A2 corresponding to the applicable object identifier B includes two system clauses of X1 and X3; and so on.
  • Step 310 Add the system description information and the system sub-file corresponding to each applicable object identifier to the corresponding association information tree.
  • the server generates an information node according to the system description information, associates the corresponding system sub-file to the information node, and adds the information node to the associated information tree corresponding to the same applicable object identifier. Specifically, after the server adds the system information to the corresponding target information tree, the server acquires the corresponding associated information tree corresponding to the target information tree according to the applicable object identifier recorded by the system file. It is easy to understand that the server only needs to obtain the associated information tree corresponding to the applicable object identifier of the system file record. For example, the institutional information classification is added to three target information trees, including the target information tree M.
  • the target information tree M corresponds to the applicable object identifiers including A, B, C, D, E, and E. Assume that the system file only includes information content applicable to A, B, C, D, and E according to the above example, the server only needs to obtain the target information.
  • the server generates an information node according to the system description information, and associates the split multiple system sub-files with the information node.
  • the server adds multiple information nodes associated with different system sub-files to the associated information tree corresponding to the same applicable object identifier. For example, in the above example, the association has added system subfile information of the nodes A1 to object information tree M applicable object ID A corresponding association information tree M A; and is associated with adding system subfile information of the node A2 to the target information
  • the tree M corresponds to the associated information tree M B corresponding to the object identifier B , and so on.
  • the system documents that are applicable to the system information of different positions are recorded, and the system clauses that need to be executed or understood for each position are selected to meet the individual needs of different positions.
  • Different posts are used to construct an associated information tree that only contains the content of the corresponding post requirements, and the process of generating all associated information trees is fully automated, saving time and effort; subsequent users only need to perform system query based on the associated information tree applicable to them, and can also improve Institutional query efficiency.
  • classifying the system information, and adding the system information to the preset one or more target information trees according to the classification result comprises: segmenting the system information to obtain a corresponding original word set; the original word set includes more Original words; synonymous expansion of each original word, generate a set of extended words corresponding to each original word; form an extended system information set corresponding to the system information according to each expanded word set; input the extended system information set into a preset system management
  • the model obtains the target category corresponding to the system information; obtains the category label corresponding to each of the plurality of target information trees, filters the target information tree including the category label corresponding to the target category, and adds the system information to the target information tree obtained by the screening.
  • the server segments the system information through a word segmentation algorithm to obtain a collection of original words.
  • the original set of words includes a plurality of original words.
  • words that have a small effect on the classification such as stop words, modal particles, and punctuation marks, are removed, thereby improving the efficiency of subsequent feature extraction.
  • a stop word refers to a word in the system information that appears more than a preset threshold but has little practical meaning, such as me, he, etc.
  • the terminal may also pre-specify the category information of the system information, so that the server can incorporate the system information into the corresponding target information tree according to the category information. If the system description information already contains category information of the system information, the system information can be added to the corresponding target information tree according to the category information. If the system description information does not include the category information of the system information, the system information may be classified and managed according to the system information processing method provided by the present application.
  • the server separately obtains the synonym corresponding to each original word in the original word set, and forms the extended word set by the original word and the corresponding synonym.
  • Synonyms refer to words that have the same or similar meaning as the original words.
  • the original words are “not allowed”, and the synonyms can be “no”, “forbidden”, “avoided”, “cancelled”, etc., and the original words and corresponding synonyms are formed. Expand the collection of words, such as the original words "not allowed” corresponding to the set of extended words as ⁇ no, no, prohibit, avoid, eliminate ⁇ .
  • each original word in the original word set has a corresponding extended word set, such as a corresponding extended word set of a is ⁇ a, a1, a2 ⁇ , b corresponding
  • the set of extended words is ⁇ b, b1, b2, b3 ⁇
  • the set of extended words corresponding to c is ⁇ c, c1, c2 ⁇ .
  • the server arbitrarily selects one word from the set of extended words corresponding to each original word according to the order in which the original words appear in the system information, and forms an extended system information in order.
  • different extended system information is formed, and different extended system information constitutes an expanded system information set.
  • the server obtains a Cartesian product for the set of extended words corresponding to each original word, and forms a set of extended system information composed of different extended system information.
  • the Cartesian product of the two sets X and Y also known as the direct product, is expressed as X ⁇ Y.
  • the first object is a member of X and the second object is one of all possible ordered pairs of Y.
  • the institutional management model is for determining a target category corresponding to the input from among a plurality of candidate types based on the input.
  • the system management model can be a model obtained by training such as logistic regression algorithm and support vector machine algorithm.
  • the system management model can be formed by multiple sub-management model connections. Since the input of the trained system management model is an expanded set of extended system information, the expanded information of each extended system expresses the same or similar meaning as the institutional information, and improves the effective coverage of the institutional information, so as to be input later. After the trained system management model, the accuracy of the target category can be improved.
  • the server obtains the category label corresponding to the target category, and filters one or more target information trees including the obtained category label.
  • the server generates an information node according to the system description information, and detects whether the same information node already exists in the target information tree obtained by the screening. If not, the server associates the system file to the information node, and adds the information node associated with the system file to the filtered target information tree.
  • the server determines, according to the system description information, whether the generated information node belongs to a parallel node or a parent child node with the same information node that already exists. When the generated information node and the existing information node belong to the parallel node, the server distinguishes the generated information node from the existing information node, and adds the marked information node to the corresponding target information tree.
  • the system file is associated with the information node after the difference mark.
  • the server When the generated information node and the existing same information node belong to the parallel node, the server describes and defines the generated information node according to the system description information, that is, extracts the keyword in the system description information, and generates the generated keyword pair.
  • the information node performs semantic expansion.
  • the information node generated according to the name of the system is the “company welfare management system”
  • the keyword “research and development department” is extracted from the system description information
  • the information node after the semantic expansion may be the “company development department welfare management system”.
  • the server adds the semantically expanded information node as a child node of the existing same information node to the corresponding target information tree, and associates the system file to the child node.
  • the extended word set corresponding to each original word is formed first, and then the expanded system information set is formed by expanding the word set, thereby greatly expanding the expansion degree of the extended system information, and the extended extended system information is expressed and institutional information.
  • the same or similar meanings improve the effective coverage of institutional information, so that after the input of the trained system management model, the accuracy of the target category can be improved, and the system information can be accurately incorporated into the corresponding target information tree, and the system can be improved. Information classification efficiency and accuracy.
  • pushing the plurality of file fragments to the first terminal comprises: randomly generating a key string when receiving the system learning request; acquiring a pre-stored private key, and using the private key to perform the key string
  • Asymmetric encryption sends the encrypted key string to the first terminal; when splitting the file fragment, the sensitive field in the positioning system sub-file uses the randomly generated key string to symmetrically encrypt the sensitive field to generate a file.
  • Asymmetric encryption is more secure, but when a large amount of sensitive information is involved in the transmitted file, the encryption and decryption time takes a long time and is slow. Therefore, asymmetric encryption is only suitable for encrypting a small amount of data.
  • Symmetric encryption requires a fixed private key at the terminal. There is a certain security risk, and security cannot be guaranteed.
  • the organic combination of symmetric encryption and asymmetric encryption can not only quickly encrypt a large number of sensitive fields, but also make the transmission and storage of system information more secure and reliable.
  • the server when receiving the system query request, the server generates a key string according to the set random algorithm, and stores the generated key string in the memory. When the key string is stored in the memory, the generation time of the key string and the corresponding information node identifier are also associated.
  • the format of the stored content may be: information node A + generation time + key string.
  • the server asymmetrically encrypts the randomly generated key string using the pre-stored private key, and sends the encrypted key string to the first terminal.
  • the key string is stored in the memory, that is, the pre-stored private key is obtained to asymmetrically encrypt the key string, and the encrypted key is obtained. Strings are stored. When the system sub-file satisfying the query condition is found, the stored encrypted key string is directly sent to the first terminal to avoid slowing down the request.
  • the server parses the found system sub-file to obtain the file content, searches the sensitive information contained in the system sub-file according to the set sensitive information search rule to locate the sensitive field corresponding to the sensitive information, and uses the randomly generated key string.
  • a key string that is asymmetrically encrypted without a preset private key symmetrically encrypts the located sensitive field to generate a system ciphertext. Only sensitive fields in the generated system ciphertext are displayed in secret by the encrypted string, and other contents are displayed in the original plaintext.
  • sensitive information in the system sub-file may also be marked in advance, such as text bolding or highlighting sensitive information in different colors. When locating sensitive fields in a file, just look up the tag location. After the sensitive field is encrypted, the mark of the sensitive field can be removed or removed, and the configuration can be configured as needed.
  • the server returns the generated system ciphertext to the first terminal, so that the corresponding user performs system learning at the first terminal.
  • the system ciphertext can be decrypted by the encrypted key string obtained from the server to obtain the original plaintext file. Specifically, the first terminal decrypts the encrypted key string by using a public key pre-published by the server to obtain a key string; and then decrypts the sensitive field in the system ciphertext by using the key string.
  • the public key private key pair used by asymmetric encryption is dynamically generated and updated periodically.
  • the server obtains an operation behavior log generated by the first terminal during the monitoring period on the system ciphertext operation.
  • the operational behavior log refers to a log formed by monitoring operational events of the user acting on the service terminal.
  • the operation event may include an system query operation, a download operation, a decryption operation, or a forwarding operation on the system ciphertext.
  • the server extracts the operation behavior log of the corresponding user in multiple service terminals according to the preset time frequency.
  • the server calculates the information leakage risk value corresponding to the service terminal according to the operation behavior log. Specifically, the server parses the extracted operation behavior log to obtain corresponding operation behavior data.
  • the operational behavior data includes the number of download failures of the system ciphertext, the number of decryption failures, or the number of failed forwardings.
  • the server calculates the information leakage risk value corresponding to the service terminal according to the number of download failures, the number of decryption failures, and the number of failed forwardings of the system ciphertext.
  • the server monitors the information leakage risk value to exceed the threshold.
  • the server When the information leakage risk value exceeds the threshold, the server generates an information leakage warning according to the information leakage risk value exceeding the threshold and the corresponding user identifier.
  • the information leakage warning has multiple implementation modes. One implementation manner is that the server generates a user behavior monitoring report according to the user identifier and the corresponding information leakage risk value, and the information leakage risk value exceeding the threshold value and the corresponding user are displayed in the user behavior monitoring report. The logo is marked differently.
  • the server sends an information leakage warning to the monitoring terminal, so as to prompt the monitoring terminal to take information leakage prevention measures, such as reducing the operation authority of the corresponding user to the business system.
  • the monitoring terminal is a pre-designated terminal with monitoring authority. It is easy to understand that the monitoring terminal can include a user terminal to directly prompt the corresponding user.
  • the key string is asymmetrically encrypted, the security of the key string is effectively ensured, and only asymmetrically encrypting and decrypting the key string with a small amount of data does not affect encryption and decryption. effectiveness. Symmetric encryption and decryption is adopted for sensitive fields. Even if the number of privacy fields is large, it can be quickly encrypted and decrypted. With the random dynamic key generation method, the encryption and decryption efficiency can be ensured and the information security can be effectively guaranteed.
  • the information leakage risk value corresponding to the service terminal can be calculated; when the information leakage risk value exceeds the threshold In time, the system query authority of the service terminal can be reduced in time to further improve information security.
  • the file segment includes a document fragment; the learning event includes a document closing event; capturing a learning event for the file segment that occurs at the first terminal, and acquiring the institutional learning data corresponding to the learning event includes: capturing a pair generated by the first terminal The actual reading time of the document fragment; the data volume of the document fragment is obtained, and the normal reading time corresponding to the document fragment is calculated according to the data amount; when the document closing event is captured, the reading position of the document fragment is recorded, and a random evaluation questionnaire is generated according to the document fragment, The random evaluation questionnaire is sent to the first terminal; the answer information of the random evaluation questionnaire returned by the first terminal within the preset duration is received, the answer information is scored, and the score value is obtained; according to the measured score value, the actual reading time, and the regular reading time. And calculating an effective learning time corresponding to the first terminal.
  • the fragment obtained can be a document fragment, a video clip, and the like.
  • the corresponding regular reading time is different.
  • the corresponding regular viewing time is different.
  • the video clip has a corresponding play time, and the regular viewing time is a length of time shorter than the play time.
  • the server captures a learning event for the document segment that occurs at the first terminal, and acquires system learning data corresponding to the learning event.
  • Institutional learning data includes the actual reading time of a document fragment.
  • the server calculates the data amount of the document segment, and calculates the regular reading time corresponding to the document segment according to the data amount.
  • Learning events include document close events. When the document close event is captured, the server records the reading position of the document fragment, which is convenient for the user to learn the next system.
  • the server generates a random assessment questionnaire based on the document fragments and transmits the random assessment questionnaire to the first terminal.
  • the assessment questionnaire included multiple random questions.
  • the server receives the answer information of the random question returned by the first terminal within the preset duration, and scores the answer information to obtain a score value.
  • the server calculates the time deviation between the actual reading time and the regular reading time.
  • the server comprehensively calculates the effective learning time corresponding to the first terminal according to the measured score value and the time deviation and the preset corresponding weight factors, so that the effective learning time is more accurate.
  • the time deviation between the actual reading time and the regular reading time it can be determined whether the user is cheating in the system learning process; by scoring the answer information of the random question, the effect of the user learning the system can be judged; The two dimensions of information and time deviation calculate the effective learning time of the user, making the measurement of the effective learning time more realistic and more accurate.
  • FIGS. 2 and 3 are sequentially displayed in accordance with the indication of the arrows, these steps are not necessarily performed in the order indicated by the arrows. Except as explicitly stated herein, the execution of these steps is not strictly limited, and the steps may be performed in other orders. Moreover, at least some of the steps in FIGS. 2 and 3 may include a plurality of sub-steps or stages, which are not necessarily performed at the same time, but may be performed at different times, or The order of execution of the stages is also not necessarily sequential, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.
  • an institutional information processing apparatus including: an system query module 602, a system splitting module 604, and a learning monitoring module 606, wherein:
  • the system query module 602 is configured to receive an institutional learning request sent by the first terminal, where the system learning request carries the applicable object identifier and the query condition, and acquires an associated information tree corresponding to the applicable object identifier; the associated information tree includes multiple information nodes and each Multiple system sub-files associated with the information node; find information nodes that satisfy the query conditions in the associated information tree.
  • the system splitting module 604 is configured to obtain a system sub-file corresponding to the found information node, split the system sub-file into a plurality of file segments, and push the plurality of file segments to the first terminal.
  • the learning monitoring module 606 is configured to capture a learning event of a file segment generated by the first terminal, and acquire system learning data corresponding to the learning event; the system learning data includes an effective learning time; when the effective learning time reaches a threshold, the target resource is acquired, and The target resource is transferred to the first terminal.
  • the apparatus further includes an information archiving module 608 for monitoring system information issued by the second terminal; the system information includes system description information and associated system files; the system file includes multiple system terms and each system The applicable object identifier corresponding to the clause; classifying the system information, adding the system information to the preset one or more target information trees according to the classification result; acquiring a plurality of associated information trees corresponding to the target information tree; each associated information tree has Corresponding applicable object identifier; split the system file, use the system clause corresponding to each applicable object identifier to generate the system sub-file corresponding to the applicable object identifier; add the system description information and the system sub-file corresponding to each applicable object identifier To the corresponding associated information tree.
  • the system information includes system description information and associated system files
  • the system file includes multiple system terms and each system The applicable object identifier corresponding to the clause; classifying the system information, adding the system information to the preset one or more target information trees according to the classification result; acquiring a plurality of associated information trees corresponding to the
  • the information archiving module 608 is further configured to perform word segmentation on the system information to obtain a corresponding original word set;
  • the original word set includes a plurality of original words; synonymously expand each original word to generate each original word corresponding a set of extended words; forming a set of extended system information corresponding to the system information according to each set of extended words; inputting the expanded system information set into a preset institutional management model, obtaining a target category corresponding to the institutional information; acquiring a plurality of target information trees respectively corresponding
  • the category labeling screen filters the target information tree including the category label corresponding to the target category, and adds the system information to the filtered target information tree.
  • the system splitting module 604 is further configured to randomly generate a key string when receiving the system learning request; obtain a pre-stored private key, and asymmetrically encrypt the key string by using a private key, Sending the encrypted key string to the first terminal; when splitting the obtained file fragment, the sensitive field in the positioning system subfile uses a randomly generated key string to symmetrically encrypt the sensitive field, and generates a system corresponding to the file fragment.
  • the ciphertext is sent to the first terminal; the learning monitoring module 606 is further configured to obtain the number of decryption failures of the first terminal in the monitoring period for the ciphertext operation; and calculate the information leakage risk corresponding to the service terminal according to the number of decryption failures Value; when the information leakage risk value exceeds the threshold, the system query authority of the first terminal is lowered.
  • system splitting module 604 is further configured to obtain a file type of the system sub-file; obtain a corresponding data amount threshold according to the file type; and split the system sub-file according to the data quantity threshold to obtain multiple files. Fragment; according to the splitting order, multiple file segments are sequentially pushed to the first terminal.
  • the file fragment includes a document fragment; the learning event includes a document close event; the learning monitoring module 606 is further configured to capture an actual reading time of the document fragment generated by the first terminal; and obtain a data amount of the document fragment according to the data. Calculating the normal reading time corresponding to the document segment; when the document closing event is captured, recording the reading position of the document segment, generating a random evaluation questionnaire according to the document segment, and transmitting the random evaluation questionnaire to the first terminal; receiving the first terminal is preset The answer information of the random evaluation questionnaire returned within the duration, the answer information is scored, and the score value is obtained; and the effective learning time corresponding to the first terminal is calculated according to the measured score value, the actual reading time, and the regular reading time.
  • the learning monitoring module 606 is further configured to: when the effective learning time reaches the threshold, send a resource extraction page to the first terminal; and monitor a resource extraction operation that occurs by the first terminal on the resource extraction page, according to the resource extraction operation, Obtain a target resource of a random share; transfer the obtained target resource to the first terminal.
  • system information processing device For the specific definition of the system information processing device, reference may be made to the above limitation of the system information processing method, and details are not described herein again.
  • system information processing apparatuses may be implemented in whole or in part by software, hardware, and a combination thereof.
  • Each of the above modules may be embedded in or independent of the processor in the computer device, or may be stored in a memory in the computer device in a software form, so that the processor invokes the operations corresponding to the above modules.
  • a computer device which may be a server, the internal structure of which may be as shown in FIG.
  • the computer device includes a processor, memory, network interface, and database connected by a system bus.
  • the processor of the computer device is used to provide computing and control capabilities.
  • the memory of the computer device includes a non-volatile storage medium, an internal memory.
  • the non-volatile storage medium stores an operating system, computer readable instructions, and a database.
  • the internal memory provides an environment for operation of an operating system and computer readable instructions in a non-volatile storage medium.
  • the database of the computer device is used to store institutional information.
  • the network interface of the computer device is used to communicate with an external terminal via a network connection.
  • FIG. 6 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation of the computer device to which the solution of the present application is applied.
  • the specific computer device may It includes more or fewer components than those shown in the figures, or some components are combined, or have different component arrangements.
  • One or more non-volatile storage media storing computer readable instructions, when executed by one or more processors, causing one or more processors to implement a system as provided in any one embodiment of the present application The steps of the information processing method.
  • Non-volatile memory can include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory.
  • Volatile memory can include random access memory (RAM) or external cache memory.
  • RAM is available in a variety of formats, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronization chain.
  • SRAM static RAM
  • DRAM dynamic RAM
  • SDRAM synchronous DRAM
  • DDRSDRAM double data rate SDRAM
  • ESDRAM enhanced SDRAM
  • Synchlink DRAM SLDRAM
  • Memory Bus Radbus
  • RDRAM Direct RAM
  • DRAM Direct Memory Bus Dynamic RAM
  • RDRAM Memory Bus Dynamic RAM

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Abstract

A regulation information processing method, comprising: receiving a regulation learning request sent by a first terminal, wherein the regulation learning request carries an applicable object identifier and a query condition; acquiring an associated information tree corresponding to the applicable object identifier, wherein the associated information tree comprises multiple information nodes and respective multiple regulation sub-files associated therewith; querying the associated information tree for an information node satisfying a query condition; acquiring a regulation sub-file corresponding to the queried information node, splitting the regulation sub-file into multiple file segments, and pushing the multiple file segments to the first terminal; capturing an event of learning a file segment occurring on the first terminal to acquire regulation learning data corresponding to the learning event, wherein the regulation learning data comprises an effective learning time; and when the effective learning time reaches a threshold, acquiring a target resource and transferring the target resource to the first terminal.

Description

制度信息处理方法、装置、计算机设备和存储介质Institutional information processing method, device, computer device and storage medium
本申请要求于2018年4月9日提交中国专利局，申请号为2018103130429，申请名称为“制度信息处理方法、装置、计算机设备和存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。This application claims the priority of the Chinese Patent Application entitled "Institutional Information Processing Method, Apparatus, Computer Equipment, and Storage Media" filed on April 9, 2018, the Chinese Patent Office, the application number is 2018103130429, the entire contents of which are incorporated by reference. Combined in this application.
技术领域Technical field
本申请涉及一种制度信息处理方法、装置、计算机设备和存储介质。The present application relates to a system information processing method, apparatus, computer device and storage medium.
背景技术Background technique
企业标准化是对企业生产经营与管理等活动中的重复性事物和概念，通过制订、发布和实施制度规范达到统一，以提高企业管理水平。制度规范(以下简称“制度”)是员工在生产经营活动中须共同遵守的规定和准则，包括法律与政策、企业组织结构、管理制度、岗位职责、技术标准、工作流程等制度文件。对于已发布制度，企业需要不断进行制度宣传，督促员工进行制度学习，进而保证制度能够在实际业务活动中发挥指导意义。随着企业规模增大，相应的制度信息越来越多。但发明人意识到，这种方式需要占用大段的工作时间，使得制度宣传成本和制度学习成本均不同程度增加。Enterprise standardization is a repetitive thing and concept in the activities of production, management and management of enterprises. It is unified through the formulation, release and implementation of system norms to improve the management level of enterprises. Institutional norms (hereinafter referred to as "institutions") are the rules and guidelines that employees must abide by in their production and operation activities, including laws and policies, organizational structure, management systems, job responsibilities, technical standards, and work processes. For the published system, enterprises need to continuously carry out system publicity and urge employees to carry out institutional learning, so as to ensure that the system can play a guiding role in actual business activities. As the size of the company increases, so does the corresponding institutional information. However, the inventor realized that this method requires a large amount of working time, which increases the system promotion cost and the system learning cost.
发明内容Summary of the invention
根据本申请公开的各种实施例，提供一种制度信息处理方法、装置、计算机设备和存储介质。According to various embodiments disclosed herein, a system information processing method, apparatus, computer device, and storage medium are provided.
一种制度信息处理方法包括：接收第一终端发送的制度学习请求，所述制度学习请求携带了适用对象标识和查询条件；获取所述适用对象标识对应的关联信息树；所述关联信息树包括多个信息节点及每个所述信息节点关联的多个制度子文件；在所述关联信息树中查找满足所述查询条件的信息节点；获取查找到的信息节点对应的制度子文件，将所述制度子文件拆分为多个文件片段，将多个所述文件片段推送至所述第一终端；捕获所述第一终端发生的对所述文件片段的学习事件，获取所述学习事件对应的制度学习数据；所述制度学习数据包括有效学习时间；及当所述有效学习时间达到阈值时，获取目标资源，将所述目标资源转移至所述第一终端。An institutional information processing method includes: receiving an institutional learning request sent by a first terminal, where the system learning request carries an applicable object identifier and a query condition; and acquiring an associated information tree corresponding to the applicable object identifier; the associated information tree includes a plurality of information nodes and a plurality of system sub-files associated with each of the information nodes; searching for an information node that satisfies the query condition in the association information tree; and acquiring a system sub-file corresponding to the found information node, The system sub-file is split into a plurality of file segments, and the plurality of the file segments are pushed to the first terminal; the learning event of the file segment generated by the first terminal is captured, and the learning event is acquired. Institutional learning data; the institutional learning data includes an effective learning time; and when the effective learning time reaches a threshold, acquiring a target resource, and transferring the target resource to the first terminal.
一种制度信息处理装置包括：制度查询模块，用于接收第一终端发送的制度学习请求，所述制度学习请求携带了适用对象标识和查询条件；获取所述适用对象标识对应的关联信息树；所述关联信息树包括多个信息节点及每个所述信息节点关联的多个制度子文件；在所述关联信息树中查找满足所述查询条件的信息节点；制度拆分模块，用于获取查找到的信息节点对应的制度子文件，将所述制度子文件拆分为多个文件片段，将多个所述文件片段推送至所述第一终端；学习监控模块，用于捕获所述第一终端发生的对所述文件片段的 学习事件，获取所述学习事件对应的制度学习数据；所述制度学习数据包括有效学习时间；及当所述有效学习时间达到阈值时，获取目标资源，将所述目标资源转移至所述第一终端。An system information processing apparatus includes: an system query module, configured to receive an institutional learning request sent by a first terminal, where the system learning request carries an applicable object identifier and a query condition; and acquires an associated information tree corresponding to the applicable object identifier; The association information tree includes a plurality of information nodes and a plurality of system sub-files associated with each of the information nodes; searching, in the association information tree, an information node that satisfies the query condition; and an system splitting module for acquiring a system sub-file corresponding to the found information node, splitting the system sub-file into a plurality of file segments, and pushing a plurality of the file segments to the first terminal; and a learning monitoring module, configured to capture the a learning event for the file segment generated by a terminal, acquiring institutional learning data corresponding to the learning event; the institutional learning data includes an effective learning time; and when the effective learning time reaches a threshold, acquiring a target resource, The target resource is transferred to the first terminal.
一种计算机设备，包括存储器和一个或多个处理器，存储器中存储有计算机可读指令，计算机可读指令被处理器执行时实现本申请任意一个实施例中提供的制度信息处理方法的步骤。A computer apparatus comprising a memory and one or more processors having stored therein computer readable instructions that, when executed by a processor, implement the steps of the system information processing method provided in any one of the embodiments of the present application.
一个或多个存储有计算机可读指令的非易失性存储介质，计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器实现本申请任意一个实施例中提供的制度信息处理方法的步骤。One or more non-volatile storage media storing computer readable instructions, when executed by one or more processors, causing one or more processors to implement a system as provided in any one embodiment of the present application The steps of the information processing method.
本申请的一个或多个实施例的细节在下面的附图和描述中提出。本申请的其它特征和优点将从说明书、附图以及权利要求书变得明显。Details of one or more embodiments of the present application are set forth in the accompanying drawings and description below. Other features and advantages of the present invention will be apparent from the description, drawings and claims.
附图说明DRAWINGS
为了更清楚地说明本申请实施例中的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其它的附图。In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings to be used in the embodiments will be briefly described below. Obviously, the drawings in the following description are only some embodiments of the present application, Those skilled in the art can also obtain other drawings based on these drawings without any creative work.
图1为根据一个或多个实施例中制度信息处理方法的应用场景图；1 is an application scenario diagram of a system information processing method according to one or more embodiments;
图2为根据一个或多个实施例中制度信息处理方法的流程示意图。2 is a flow diagram of a method of processing institutional information in accordance with one or more embodiments.
图3为根据一个或多个实施例中构建关联信息树步骤的流程示意图。3 is a flow diagram of the steps of constructing an associated information tree in accordance with one or more embodiments.
图4为根据一个或多个实施例中制度信息处理方法中目标信息树的示意图。4 is a schematic diagram of a target information tree in a system information processing method in accordance with one or more embodiments.
图5为根据一个或多个实施例中制度信息处理方法中关联信息树的示意图。FIG. 5 is a schematic diagram of an associated information tree in a system information processing method in accordance with one or more embodiments.
图6为根据一个或多个实施例中制度信息处理装置的结构框图。FIG. 6 is a block diagram showing the structure of an institutional information processing apparatus according to one or more embodiments.
图7为根据一个或多个实施例中计算机设备的框图。FIG. 7 is a block diagram of a computer device in accordance with one or more embodiments.
具体实施方式detailed description
为了使本申请的技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。In order to make the technical solutions and advantages of the present application more clear, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It is understood that the specific embodiments described herein are merely illustrative of the application and are not intended to be limiting.
本申请提供的制度信息处理方法，可以应用于如图1所示的应用环境中。第一终端102与服务器104通过网络进行通信。第二终端106与服务器104通过网络进行通信。第一终端102和第二终端106可以但不限于是各种个人计算机、笔记本电脑、智能手机、平板电脑和便携式可穿戴设备。第一终端102为业务终端，用户可以在第一终端102进行制度学习等操作。第二终端106为制度管理终端，用户可以在第二终端106进行制度起草、意见征集、审批和发布等。第一终端102与第二终端106可以同一终端，也可以是不同的终端。服务器104可以用独立的服务器或者是多个服务器组成的服务器集群来实现。The system information processing method provided by the present application can be applied to an application environment as shown in FIG. 1. The first terminal 102 communicates with the server 104 over a network. The second terminal 106 communicates with the server 104 over a network. The first terminal 102 and the second terminal 106 can be, but are not limited to, various personal computers, notebook computers, smart phones, tablets, and portable wearable devices. The first terminal 102 is a service terminal, and the user can perform operations such as system learning at the first terminal 102. The second terminal 106 is a system management terminal, and the user can perform system drafting, opinion collection, approval, and release in the second terminal 106. The first terminal 102 and the second terminal 106 may be the same terminal or different terminals. The server 104 can be implemented by a stand-alone server or a server cluster composed of a plurality of servers.
当用户需要通过第一终端102进行制度学习时，向服务器104发送制度学习请求。 制度学习请求携带了适用对象标识和查询条件。服务器104获取适用对象标识对应的关联信息树。关联信息树包括多个信息节点及每个信息节点关联的制度子文件。服务器104在关联信息树中查找是否存在满足查询条件的信息节点。若存在，服务器104获取与满足查询条件的信息节点关联的制度子文件，将制度子文件拆分为多个文件片段，将多个文件片段推送至第一终端102。用户可以在第一终端102进行制度学习。第一终端102预先设置了埋点。当需要对被埋点控件进行触按操作时，第一终端102拦截该触按操作对应的学习事件，并将该学习事件上报至服务器104。服务器104捕获第一终端发生的对制度子文件的学习事件，获取学习事件对应的制度学习数据。制度学习数据包括用户标识及对应的有效学习时间。服务器判断有效学习时间是否达到阈值，若达到，则获取目标资源，将目标资源转移至第一终端102。上述制度学习过程，将制度子文件拆分为多个数据量小的文件片段，使用户可以利用碎片化时间进行制度学习；在有效学习时间达到阈值时，给予目标资源奖励，提高用户进行制度学习积极性，自动对用户的制度学习情况进行监控，降低制度宣传成本和学习成本。When the user needs to perform institutional learning through the first terminal 102, an institutional learning request is sent to the server 104. The institutional learning request carries the applicable object identification and query conditions. The server 104 acquires an association information tree corresponding to the applicable object identifier. The association information tree includes a plurality of information nodes and a system sub-file associated with each information node. The server 104 looks in the association information tree whether there is an information node that satisfies the query condition. If so, the server 104 acquires a system subfile associated with the information node that satisfies the query condition, splits the system subfile into a plurality of file segments, and pushes the plurality of file segments to the first terminal 102. The user can perform institutional learning at the first terminal 102. The first terminal 102 has previously set a buried point. When a touch operation is required on the buried point control, the first terminal 102 intercepts the learning event corresponding to the touch operation and reports the learning event to the server 104. The server 104 captures the learning event of the system sub-file generated by the first terminal, and acquires the system learning data corresponding to the learning event. Institutional learning data includes user identification and corresponding effective learning time. The server determines whether the effective learning time reaches the threshold. If yes, the target resource is acquired, and the target resource is transferred to the first terminal 102. In the above-mentioned system learning process, the system sub-file is divided into a plurality of file fragments with small data volume, so that the user can use the fragmentation time for system learning; when the effective learning time reaches the threshold, the target resource is rewarded, and the user is promoted to system learning. Enthusiasm, automatically monitor the user's institutional learning, reduce system promotion costs and learning costs.
在其中一个实施例中，如图2所示，提供了一种制度信息处理方法，以该方法应用于图1中的服务器为例进行说明，包括以下步骤：In one embodiment, as shown in FIG. 2, a system information processing method is provided. The method is applied to the server in FIG. 1 as an example, and includes the following steps:
步骤202，接收第一终端发送的制度学习请求，制度学习请求携带了适用对象标识和查询条件。Step 202: Receive an institutional learning request sent by the first terminal, where the system learning request carries the applicable object identifier and the query condition.
服务器中存储了多种关联信息树。关联信息树包括多个信息节点及每个信息节点关联的制度子文件。当有新发布的制度信息，服务器对制度信息进行分类和拆分处理，将拆分得到的制度信息添加至相应的关联信息树。服务器在生成每个适用对象标识对应的关联信息树后，将关联信息树推送至相应岗位对应的第一终端，供相应岗位用户参考查询学习。A variety of associated information trees are stored in the server. The association information tree includes a plurality of information nodes and a system sub-file associated with each information node. When there is newly released institutional information, the server classifies and splits the system information, and adds the split system information to the corresponding associated information tree. After generating the associated information tree corresponding to each applicable object identifier, the server pushes the associated information tree to the first terminal corresponding to the corresponding post, so that the corresponding post user can refer to the query for learning.
用户可以在业务终端通过业务***进行制度查询学习。第一终端根据用户对关联信息树的查询操作，触发制度查询请求。将制度查询请求发送至服务器。制度查询请求包括第一查询请求和第二查询请求。例如，第二终端检测到鼠标停留在某个信息节点的时间超过阈值，则向服务器发送第一查询请求。第二终端检测到鼠标在某个信息节点的鼠标点击操作，则向服务器发送第二查询请求。第一查询请求携带了用户标识和查询条件。查询条件可以是一个或多个关键词。The user can conduct system query learning through the business system at the business terminal. The first terminal triggers the system query request according to the query operation of the user on the associated information tree. Send an institutional query request to the server. The system query request includes a first query request and a second query request. For example, when the second terminal detects that the mouse stays at a certain information node exceeds a threshold, the second terminal sends a first query request to the server. When the second terminal detects a mouse click operation of the mouse on an information node, the second terminal sends a second query request to the server. The first query request carries the user identification and query conditions. The query condition can be one or more keywords.
步骤204，获取适用对象标识对应的关联信息树；关联信息树包括多个信息节点及每个信息节点关联的多个制度子文件。Step 204: Acquire an association information tree corresponding to the applicable object identifier. The association information tree includes multiple information nodes and multiple system sub-files associated with each information node.
步骤206，在关联信息树中查找满足查询条件的信息节点。Step 206: Find an information node that satisfies the query condition in the association information tree.
服务器根据第一查询请求，获取用户标识对应的适用对象标识。用户标识用于定位查询操作事件的操作对象，可以是业务***的登录账号或业务终端的IP地址(Internet Protocol Address，互联网协议地址)中的至少一种。The server obtains the applicable object identifier corresponding to the user identifier according to the first query request. The user identifier is used to locate the operation object of the query operation event, and may be at least one of a login account of the service system or an IP address (Internet Protocol Address) of the service terminal.
根据适用对象标识获取对应的关联信息树，在获取到的关联信息树中查找是否存在 满足查询条件的信息节点。关联信息树中每个信息节点关联有对应的信息摘要。信息摘要记录了相应制度信息的用途、主要内容简介或适用范围等。当信息节点或其关联的信息摘要中包含查询条件中多个关键词则表示该信息节点满足查询条件。Obtain the corresponding association information tree according to the applicable object identifier, and search for the information node that satisfies the query condition in the obtained association information tree. Each information node in the associated information tree is associated with a corresponding information digest. The information summary records the purpose of the corresponding system information, the main content introduction or the scope of application. When the information node or its associated information digest contains multiple keywords in the query condition, it indicates that the information node satisfies the query condition.
当存在满足查询条件的信息节点时，服务器获取该信息节点关联的信息摘要，将信息摘要返回至第一终端。信息摘要可以是根据制度描述信息生成的。第一终端弹窗展示该目录节点对应的信息摘要，以便用户判断该信息节点是否为自己需要查找的制度信息。如果是，再通过第二查询请求向服务器进一步获取对应的条款详细信息，以减少第一终端与服务器之间不必要的数据传输。条款详细信息可以是被点击信息节点对应的制度子文件。When there is an information node that satisfies the query condition, the server obtains the information digest associated with the information node, and returns the information digest to the first terminal. The message summary can be generated based on the system description information. The first terminal popup window displays a summary of information corresponding to the directory node, so that the user determines whether the information node is the system information that needs to be searched for. If yes, the corresponding item detailed information is further obtained from the second query request to reduce unnecessary data transmission between the first terminal and the server. The item details may be the system sub-file corresponding to the clicked information node.
步骤208，获取查找到的信息节点对应的制度子文件，将制度子文件拆分为多个文件片段，将多个文件片段推送至第一终端。Step 208: Acquire a system sub-file corresponding to the found information node, split the system sub-file into a plurality of file segments, and push the plurality of file segments to the first terminal.
服务器计算制度子文件的数据量，检测数据量是否超过阈值。该阈值可以是预先设定的，也可以是根据服务器的负载监测结果临时生成的。为了方便用户利用碎片化时间进行制度学习，当数据量超过阈值时，服务器将查询到的制度子文件拆分为多个数据量小的文件片段，将多个文件片段推送至第一终端。The server calculates the amount of data in the system subfile and detects whether the data amount exceeds the threshold. The threshold may be preset or may be temporarily generated based on the load monitoring result of the server. In order to facilitate the user to use the fragmentation time for system learning, when the data volume exceeds the threshold, the server splits the queried system sub-file into a plurality of file segments with small data volume, and pushes multiple file segments to the first terminal.
在其中一个实施例中，将制度子文件拆分为多个文件片段，将多个文件片段推送至第一终端包括：获取制度子文件的文件类型；根据文件类型，获取对应的数据量阈值；根据数据量阈值对制度子文件进行拆分，得到多个文件片段；根据拆分顺序，将多个文件片段依次推送至第一终端。In one embodiment, splitting the system sub-file into a plurality of file segments, and pushing the plurality of file segments to the first terminal comprises: acquiring a file type of the system sub-file; and obtaining a corresponding data amount threshold according to the file type; The system sub-file is split according to the data volume threshold to obtain a plurality of file segments; according to the splitting sequence, the plurality of file segments are sequentially pushed to the first terminal.
制度子文件可以是多种类型的文件，如doc文档、pdf文档、xls表格、mp3音频或avi视频等。不同文件类型可以具有不同的数据量阈值。数据量阈值可以是根据用户触发的制度学习请求临时生成的，也可以是根据对多个集群内其他服务器的负载监测结果临时生成的，还可以是预先设定的。不同类型的制度子文件对应的拆分方式可以不同。例如，当制度子文件为视频或音频时，对应的拆分方式可以是利用预设的拆分接口进行拆分。预设的拆分接口可以是OLEDB(一种应用程序接口)等。The system subfile can be multiple types of files, such as doc documents, pdf documents, xls tables, mp3 audio or avi videos. Different file types can have different data volume thresholds. The data volume threshold may be temporarily generated according to the system learning request triggered by the user, or may be temporarily generated according to the load monitoring result of other servers in the plurality of clusters, or may be preset. The splitting methods corresponding to different types of system sub-files can be different. For example, when the system sub-file is video or audio, the corresponding split mode may be split using a preset split interface. The default split interface can be OLEDB (an application program interface) and the like.
当制度子文件为文档或表格时，服务器对制度子文件进行逐行遍历，将每个适用对象标识对应的拆分表达式与制度文件中多项制度条款分别进行匹配，将制度文件中与每个拆分表达式匹配成功的制度条款拆分为一个相应适用对象标识对应的制度子文件，从而得到制度文件在多个拆分维度的制度子文件。When the system sub-file is a document or a form, the server traverses the system sub-file line by line, and matches the split expression corresponding to each applicable object identifier with multiple system terms in the system file, respectively, and The system clauses that match the successful expression of the split expression are split into a corresponding system sub-file corresponding to the applicable object identifier, thereby obtaining the system sub-file of the system file in multiple split dimensions.
服务器根据数据量阈值确定制度子文件的拆分位置。例如，制度子文件A的数据量为720M，假设数据量阈值为80M，则将制度子文件的第80M大小的位置标记为第一个拆分位置，第160M大小的位置标记为第二个拆分位置，以此类推。服务器识别每个拆分位置是否位于相邻分隔符之间。当拆分位置位于一个分隔符所在的位置时，服务器在该拆分位置对制度子文件进行拆分，得到该制度子文件对应的多个文件片段。当拆分位置位于相邻分隔符之间时，服务器在相邻分隔符中任意一个分隔符处对相应制度子文件进行拆分，即对该相邻分隔符中的前一个分隔符或后一个分隔符处进行拆分，得到制度子文件对应的多 个文件片段。服务器按照拆分顺序将多个文件片段发送至第一终端。将数据量较大的制度子文件拆分为数据量较小的文件片段后，不仅方便用户利用零碎时间进行制度学习，降低学习成本，还可以提高服务器对用户进行制度学习进度监控的精准度。The server determines the split location of the system subfile based on the data volume threshold. For example, the data volume of the system sub-file A is 720M. If the data volume threshold is 80M, the 80M size position of the system sub-file is marked as the first split position, and the 160M-size position is marked as the second split. Sub-position, and so on. The server identifies if each split location is between adjacent separators. When the split location is located at a location where the separator is located, the server splits the system subfile at the split location to obtain multiple file fragments corresponding to the system subfile. When the split position is between adjacent separators, the server splits the corresponding system subfile at any one of the adjacent separators, that is, the previous separator or the latter one of the adjacent separators The separator is split to obtain multiple file fragments corresponding to the system subfile. The server sends multiple file fragments to the first terminal in the split order. After splitting the system sub-files with large data volume into file segments with small data volume, it is not only convenient for users to use the piecemeal time to learn the system, reduce the learning cost, and also improve the accuracy of the server to monitor the progress of the system learning.
步骤210，捕获第一终端发生的对文件片段的学习事件，获取学习事件对应的制度学习数据；制度学习数据包括有效学习时间。Step 210: Capture a learning event of a file segment that occurs at the first terminal, and acquire system learning data corresponding to the learning event; the system learning data includes an effective learning time.
第一终端预先设置了埋点。当用户在第一终端对文件片段进行制度学习时，第一终端显示制度学习界面。制度学习界面包括多个控件。控件包括按钮、窗口、文本框、滚动条等。其中多个控件被预置埋点(以下称“被埋点控件”)。当用户对制度学习界面中被埋点控件进行触按操作时，第一终端拦截该触按操作对应的学习事件，并将该学习事件上报至服务器。The first terminal is pre-set with a buried point. When the user performs institutional learning on the file segment at the first terminal, the first terminal displays an institutional learning interface. The institutional learning interface includes multiple controls. Controls include buttons, windows, text boxes, scroll bars, and more. Many of the controls are pre-populated (hereinafter referred to as "buried point controls"). When the user performs a touch operation on the embedded control in the system learning interface, the first terminal intercepts the learning event corresponding to the touch operation, and reports the learning event to the server.
服务器捕获第一终端发生的对文件片段的学习事件，获取该学习事件对应的制度学习数据。制度学习数据包括一个或多个文件片段标识以及每个文件片段标识对应的学习时间等基础数据。制度学习数据还包括用户标识对应的有效学习时间等。有效学习时间可以是基础数据测算得到的。The server captures a learning event of the file segment that occurs at the first terminal, and acquires system learning data corresponding to the learning event. The institutional learning data includes basic data such as one or more file segment identifiers and learning time corresponding to each file segment identifier. The institutional learning data also includes the effective learning time corresponding to the user identification. The effective learning time can be calculated from the basic data.
步骤212，当有效学习时间达到阈值时，获取目标资源，将目标资源转移至第一终端。Step 212: When the effective learning time reaches the threshold, the target resource is acquired, and the target resource is transferred to the first terminal.
为了提高用户的制度学习积极性，服务器对用户在监控时段的有效学习时间进行监控。监控时段可以根据实际需求自由设置，如法定工作时间早上8:00至晚上9:00等。服务器判断用户的有效学习时间是否达到阈值，当有效学习时间达到阈值时，服务器获取目标资源，将目标资源转移至第一终端，对用户进行资源奖励。目标资源可以是资金资源或权限资源等，对此不作限制。例如，当目标资源为权限资源时，服务器可以根据有效学习时间提高相应用户标识对应的制度查询权限或其他对业务***的操作权限等。当目标资源为资金资源时，服务器可以根据有效学习时间获取对应份额的资金资源，根据获取到资金资源对第一终端进行数值转移。资金资源可以是代金券资源、红包资源等。容易理解，资金资源的份额可以随有效学习时间长短适应变化，也可以是随机份额，还可以是固定定额，对此不作限制。In order to improve the user's institutional learning enthusiasm, the server monitors the effective learning time of the user during the monitoring period. The monitoring period can be set freely according to actual needs, such as the legal working hours from 8:00 am to 9:00 pm. The server determines whether the effective learning time of the user reaches the threshold. When the effective learning time reaches the threshold, the server acquires the target resource, transfers the target resource to the first terminal, and rewards the user with the resource. The target resource may be a fund resource or a privilege resource, and the like. For example, when the target resource is a privileged resource, the server may increase the system query authority corresponding to the corresponding user identifier or other operation authority to the business system according to the effective learning time. When the target resource is a fund resource, the server may obtain a corresponding share of the fund resource according to the effective learning time, and perform value transfer on the first terminal according to the obtained fund resource. The capital resources may be vouchers resources, red packets resources, and the like. It is easy to understand that the share of capital resources can adapt to changes with the length of effective learning, or it can be a random share, or it can be a fixed quota, which is not limited.
在其中一个实施例中，当有效学习时间达到阈值时，获取目标资源，将目标资源转移至第一终端包括：当有效学习时间达到阈值时，向第一终端发送资源抽取页面；监测第一终端在资源抽取页面发生的资源抽取操作，根据资源抽取操作，获取随机份额的目标资源；将获取到的目标资源转移至第一终端。In one embodiment, when the effective learning time reaches the threshold, acquiring the target resource, and transferring the target resource to the first terminal includes: sending the resource extraction page to the first terminal when the effective learning time reaches the threshold; monitoring the first terminal The resource extraction operation that occurs on the resource extraction page acquires the target resource of the random share according to the resource extraction operation; and transfers the acquired target resource to the first terminal.
当有效学习时间达到阈值时，服务器向第一终端发送资源抽取页面。资源抽取页面包括资源抽取按钮和多个资源选项。服务器对第一终端在资源抽取页面发生的资源抽取操作进行监测。资源抽取操作可以是对资源抽取按钮的触按操作。当监测到资源抽取操作，服务器在多个资源选项中随机获取一种资源作为目标资源；将获取到的目标资源转移至第一终端。在一个具体的实施例中，资源抽取页面可以是抽奖页面。在制度学习时间达到阈值时，向用户提供资源抽取页面进行资源抽取，可以提高制度学习趣味性，进一步提高用户 制度学习积极性。When the effective learning time reaches the threshold, the server sends a resource extraction page to the first terminal. The resource extraction page includes a resource extraction button and a plurality of resource options. The server monitors the resource extraction operation that occurs on the resource extraction page of the first terminal. The resource extraction operation may be a touch operation on the resource extraction button. When the resource extraction operation is detected, the server randomly acquires one resource as a target resource among the multiple resource options; and transfers the acquired target resource to the first terminal. In a specific embodiment, the resource extraction page can be a lottery page. When the system learning time reaches the threshold, providing the user with a resource extraction page for resource extraction can improve the interest of the system learning and further improve the enthusiasm of the user system.
本实施例中，第一终端利用适用对象标识和查询条件生成制度学习请求，可以基于适用对象标识对应的关联信息树响应制度学习请求；在获取到的关联信息树中，可以查找满足查询条件的信息节点及关联的制度子文件；将制度子文件拆分为多个文件片段推送至第一终端，使第一终端可以基于文件片段进行制度学习；对第一终端发生的对制度子文件的学习事件进行捕获，可以获取到学习事件对应的制度学习数据；根据制度学习数据中有效学习时间是否达到阈值，可以选择进行目标资源转移。由于将制度子文件拆分为多个文件片段推送至第一终端，便于用于在第一终端利用碎片化时间进行制度学习，降低制度学习成本；自动对用户的制度学习情况进行监控，在有效学习时间达到阈值时，给予目标资源奖励，提高用户进行制度学习积极性，降低制度宣传成本和学习成本。In this embodiment, the first terminal generates an institutional learning request by using the applicable object identifier and the query condition, and may learn the request according to the associated information tree response system corresponding to the applicable object identifier; in the obtained related information tree, the first query may satisfy the query condition. Information node and associated system sub-file; splitting the system sub-file into multiple file segments and pushing it to the first terminal, so that the first terminal can perform system learning based on the file segment; learning the system sub-file generated by the first terminal The event is captured, and the system learning data corresponding to the learning event can be obtained; according to whether the effective learning time in the system learning data reaches the threshold, the target resource transfer can be selected. Since the splitting of the system sub-file into multiple file segments is pushed to the first terminal, it is convenient for the system learning by using the fragmentation time at the first terminal, thereby reducing the system learning cost; automatically monitoring the user's system learning situation, and effectively When the learning time reaches the threshold, the target resources are rewarded, the enthusiasm of the system for learning is improved, and the system promotion cost and learning cost are reduced.
在其中一个实施例中，如图3所示，在获取适用对象标识对应的关联信息树之前，还包括构建关联信息树的步骤，构建关联信息树的步骤包括：In one embodiment, as shown in FIG. 3, before the association information tree corresponding to the applicable object identifier is acquired, the step of constructing the association information tree is further included, and the step of constructing the association information tree includes:
步骤302，监测第二终端发布的制度信息；制度信息包括制度描述信息及关联的制度文件；制度文件包括多个制度条款以及每个制度条款对应的适用对象标识。Step 302: Monitor system information issued by the second terminal; the system information includes system description information and associated system files; the system file includes multiple system terms and applicable object identifiers corresponding to each system clause.
服务器对第二终端是否发布新的制度信息进行监测。制度信息包括制度描述信息及关联的制度文件。制度描述信息包括制度编码、制度名称、制度级别、发布单位、发布日期、适用对象标识或信息摘要等。制度信息可以是文本信息，也可以是语音信息、图像信息、视频信息等。如果是语音信息、图像信息或视频信息，则可先通过语音识别或图像处理，将语音信息、图像信息和视频信息转化为文本信息。制度文件包括多项制度条款以及每项制度条款对应的适用对象标识。适用对象标识是指需要执行或了解该制度的对象的标识信息，可以是岗位标识或机构标识等。The server monitors whether the second terminal issues new system information. Institutional information includes institutional description information and associated institutional documents. The system description information includes the system code, the system name, the system level, the issuing unit, the release date, the applicable object identifier or the information summary. The system information may be text information, voice information, image information, video information, and the like. If it is voice information, image information or video information, voice information, image information and video information can be converted into text information by voice recognition or image processing. The institutional document includes a number of institutional provisions and the applicable object identifier for each system clause. Applicable object identification refers to the identification information of the object that needs to perform or understand the system, and may be a post identification or an organization identification.
步骤304，对制度信息进行分类，根据分类结果将制度信息添加至预设的一个或多个目标信息树。In step 304, the system information is classified, and the system information is added to the preset one or more target information trees according to the classification result.
当监测到第二终端发布了新的制度信息时，服务器对制度信息进行分类。具体的，服务器对制度信息进行分词得到对应的原始词语集合。原始词语集合包括多个原始词语。服务器对各个原始词语进行同义扩展，生成每个原始词语对应的扩展词语集合。服务器根据各个扩展词语集合形成制度信息对应的扩展制度信息集合，将扩展制度信息集合输入预设的制度管理模型，得到制度信息对应的目标类别。When it is detected that the second terminal issues new institutional information, the server classifies the system information. Specifically, the server performs word segmentation on the system information to obtain a corresponding set of original words. The original set of words includes a plurality of original words. The server performs synonymous expansion on each original word to generate a set of extended words corresponding to each original word. The server forms a set of extended system information corresponding to the system information according to each set of extended words, and inputs the set of extended system information into a preset system management model to obtain a target category corresponding to the system information.
服务器中存储了多种目标信息树。不同目标信息树可以理解为不同的制度体系，用于存储不同类别和用途的制度信息。如图4所示，每种目标信息树包括多个信息节点及每个信息节点关联的制度文件。制度文件可以是多种类型的文件，如pdf文档、jpg图像、xls表格、mp3音频或avi视频等。不同的信息节点在目标信息树中可以按照发布时间先后排列。容易理解，一项制度信息也可以不具有关联的制度文件，也还可以具有多个关联的制度文件，对此不作限制。A variety of target information trees are stored in the server. Different target information trees can be understood as different institutional systems for storing institutional information of different categories and uses. As shown in FIG. 4, each target information tree includes a plurality of information nodes and an institutional file associated with each information node. Institutional files can be many types of files, such as pdf documents, jpg images, xls tables, mp3 audio or avi videos. Different information nodes can be arranged in the target information tree according to the release time. It is easy to understand that an institutional information may also have no associated institutional documents, and may also have multiple associated institutional documents, which is not limited.
每种目标信息树具有对应的类别标注。类别标注用于标识相应目标信息树能够包含 的信息节点的类别，如行政管理类、销售管理类或风险管理类等。服务器获取与目标类别对应的类别标注，筛选包含获取到的类别标注的一种或多种目标信息树。服务器根据制度描述信息生成信息节点。例如，可以将制度编号和/或制度名称作为信息节点。服务器将制度文件关联至该信息节点，将关联有制度文件的信息节点添加至筛选得到的目标信息树。Each target information tree has a corresponding category label. The category label is used to identify the category of the information node that the corresponding target information tree can contain, such as administrative management, sales management, or risk management. The server obtains the category label corresponding to the target category, and filters one or more target information trees including the obtained category label. The server generates an information node based on the system description information. For example, the system number and/or the system name can be used as information nodes. The server associates the system file to the information node, and adds the information node associated with the system file to the target information tree obtained by the screening.
步骤306，获取目标信息树对应的多个关联信息树；每个关联信息树具有对应的适用对象标识。Step 306: Acquire multiple association information trees corresponding to the target information tree; each associated information tree has a corresponding applicable object identifier.
每种目标信息树具有对应的多个关联信息树。目标信息树中每个信息节点具有对应的一个或多个适用对象标识。目标信息树中不同适用对象标识分别具有对应的一个关联信息树。换言之，目标信息树中包含适用对象标识的数量与对应的关联信息树的数量相等，从而每个适用对象标识对应岗位具有对应的关联信息树。Each target information tree has a corresponding plurality of associated information trees. Each information node in the target information tree has a corresponding one or more applicable object identifiers. The different applicable object identifiers in the target information tree respectively have a corresponding associated information tree. In other words, the number of applicable object identifiers in the target information tree is equal to the number of corresponding association information trees, so that each applicable object identifier corresponding post has a corresponding associated information tree.
目标信息树用于记录适用于企业全部岗位的制度信息。而关联信息树则只需记录适用于一个岗位的制度信息。每种关联信息树具有对应的适用对象标识。如图5所示，岗位1无需执行或了解信息节点4和信息节点9对应的制度，则适用对象标识“岗位1”对应的关联信息树，相对图4目标信息树不存在信息节点4和信息节点9。容易理解，关联信息树中多个信息节点的目录层级，并非一定与目标信息树一致，可以自适应调整。关联信息树仍存在的其他信息节点关联的制度文件记录的内容，与目标信息树中相应信息节点关联的制度文件记录的内容可以不同。The target information tree is used to record institutional information that applies to all positions in the enterprise. The associated information tree only needs to record the institutional information applicable to a position. Each associated information tree has a corresponding applicable object identifier. As shown in FIG. 5, if the post 1 does not need to execute or understand the system corresponding to the information node 4 and the information node 9, the associated information tree corresponding to the object identifier "post 1" is applied, and the information node 4 and the information are not present in the target information tree of FIG. Node 9. It is easy to understand that the directory hierarchy of multiple information nodes in the associated information tree is not necessarily consistent with the target information tree, and can be adaptively adjusted. The content of the system file record associated with other information nodes still existing in the associated information tree may be different from the content of the system file record associated with the corresponding information node in the target information tree.
步骤308，对制度文件进行拆分，利用每个适用对象标识对应的制度条款生成相应适用对象标识对应的制度子文件。In step 308, the system file is split, and the system sub-file corresponding to the applicable object identifier is generated by using the system clause corresponding to each applicable object identifier.
服务器根据制度文件中每个制度条款对应的适用对象标识，对制度文件中多个制度条款进行拆分，生成每个适用对象标识分别对应的制度子文件。例如，制度文件A包括X1～X4四项制度条款。其中，X1对应适用对象标识包括甲和乙，X2对应适用对象标识包括甲，X3对应适用对象标识包括甲、乙、丙、丁和戊，X4对应适用对象标识包括甲和丁。制度文件A共包括甲、乙、丙、丁和戊五个适用对象标识，对应的拆分得到五个制度子文件A1～A5。其中，适用对象标识甲对应的制度子文件A1包括X1～X4四项制度条款；适用对象标识乙对应的制度子文件A2包括X1和X3两项制度条款；如此类推。The server splits the multiple system terms in the system file according to the applicable object identifier corresponding to each system clause in the system file, and generates a system sub-file corresponding to each applicable object identifier. For example, the institutional document A includes four system clauses X1 to X4. X1 corresponds to the applicable object identifier including A and B, X2 corresponds to the applicable object identifier including A, X3 corresponds to the applicable object identifier including A, B, C, D and E, and X4 corresponds to the applicable object identifier including A and D. Institutional Document A consists of five applicable object identifiers: A, B, C, D and E. The corresponding splits are obtained in five system sub-documents A1 to A5. Among them, the system sub-file A1 corresponding to the applicable object identifier A includes four system clauses X1 to X4; the system sub-file A2 corresponding to the applicable object identifier B includes two system clauses of X1 and X3; and so on.
步骤310，将每个适用对象标识对应的制度描述信息和制度子文件添加至相应的关联信息树。Step 310: Add the system description information and the system sub-file corresponding to each applicable object identifier to the corresponding association information tree.
服务器根据制度描述信息生成信息节点，将相应制度子文件关联至信息节点，将信息节点添加至相同适用对象标识对应的关联信息树。具体的，服务器将制度信息添加至相应的目标信息树后，服务器根据制度文件记录的适用对象标识，获取目标信息树对应的相应关联信息树。容易理解，服务器只需获取制度文件记录的适用对象标识对应的关联信息树。例如，制度信息分类添加至三种目标信息树，其中包括目标信息树M。目标信息树M对应适用对象标识包括甲、乙、丙、丁、戊和己，假设依上述举例制度文件只包括适用于 甲、乙、丙、丁和戊的信息内容，则服务器只需获取目标信息树M对应的甲、乙、丙、丁和戊分别对应的关联信息树。The server generates an information node according to the system description information, associates the corresponding system sub-file to the information node, and adds the information node to the associated information tree corresponding to the same applicable object identifier. Specifically, after the server adds the system information to the corresponding target information tree, the server acquires the corresponding associated information tree corresponding to the target information tree according to the applicable object identifier recorded by the system file. It is easy to understand that the server only needs to obtain the associated information tree corresponding to the applicable object identifier of the system file record. For example, the institutional information classification is added to three target information trees, including the target information tree M. The target information tree M corresponds to the applicable object identifiers including A, B, C, D, E, and E. Assume that the system file only includes information content applicable to A, B, C, D, and E according to the above example, the server only needs to obtain the target information. The associated information tree corresponding to A, B, C, D, and E corresponding to tree M.
服务器根据制度描述信息生成信息节点，将拆分得到的多个制度子文件分别关联至信息节点。服务器将多个关联有不同制度子文件的信息节点分别添加至相同适用对象标识对应的关联信息树。例如，在上述举例中，将关联有制度子文件A1的信息节点添加至目标信息树M中适用对象标识甲对应的关联信息树M 甲；将关联有制度子文件A2的信息节点添加至目标信息树M中适用对象标识乙对应的关联信息树M 乙，如此类推。 The server generates an information node according to the system description information, and associates the split multiple system sub-files with the information node. The server adds multiple information nodes associated with different system sub-files to the associated information tree corresponding to the same applicable object identifier. For example, in the above example, the association has added system subfile information of the nodes A1 to object information tree M applicable object ID A corresponding association information tree M A; and is associated with adding system subfile information of the node A2 to the target information The tree M corresponds to the associated information tree M B corresponding to the object identifier B , and so on.
本实施例中，在制度信息发布时，将记录来了适用于不同岗位的制度信息的制度文件拆分，将每个岗位需要执行或了解的制度条款挑选出来，满足不同岗位个性化需求，为不同岗位分别构建只包含相应岗位需求内容的关联信息树，且所有关联信息树的生成过程全自动进行，省时省力；后续用户只需基于适用于自己的关联信息树进行制度查询，也可以提高制度查询效率。In this embodiment, when the system information is released, the system documents that are applicable to the system information of different positions are recorded, and the system clauses that need to be executed or understood for each position are selected to meet the individual needs of different positions. Different posts are used to construct an associated information tree that only contains the content of the corresponding post requirements, and the process of generating all associated information trees is fully automated, saving time and effort; subsequent users only need to perform system query based on the associated information tree applicable to them, and can also improve Institutional query efficiency.
在其中一个实施例中，对制度信息进行分类，根据分类结果将制度信息添加至预设的一个或多个目标信息树包括：对制度信息进行分词得到对应的原始词语集合；原始词语集合包括多个原始词语；对各个原始词语进行同义扩展，生成每个原始词语对应的扩展词语集合；根据各个扩展词语集合形成制度信息对应的扩展制度信息集合；将扩展制度信息集合输入预设的制度管理模型，得到制度信息对应的目标类别；获取多个目标信息树分别对应的类别标注，筛选包含与目标类别对应类别标注的目标信息树，将制度信息添加至筛选得到的目标信息树。In one embodiment, classifying the system information, and adding the system information to the preset one or more target information trees according to the classification result comprises: segmenting the system information to obtain a corresponding original word set; the original word set includes more Original words; synonymous expansion of each original word, generate a set of extended words corresponding to each original word; form an extended system information set corresponding to the system information according to each expanded word set; input the extended system information set into a preset system management The model obtains the target category corresponding to the system information; obtains the category label corresponding to each of the plurality of target information trees, filters the target information tree including the category label corresponding to the target category, and adds the system information to the target information tree obtained by the screening.
当监测到第一终端发布的制度信息，服务器通过分词算法对制度信息进行分词，得到原始词语集合。原始词语集合包括多个原始词语。在其中一个实施例中，得到各个原始词语后，去除停用词、语气词、标点符号等对分类影响作用小的词语，从而提高后续特征提取的效率。停用词指的是制度信息中出现频率超过预设阈值但实际意义不大的词，如我，的，他等。When the system information published by the first terminal is monitored, the server segments the system information through a word segmentation algorithm to obtain a collection of original words. The original set of words includes a plurality of original words. In one embodiment, after each original word is obtained, words that have a small effect on the classification, such as stop words, modal particles, and punctuation marks, are removed, thereby improving the efficiency of subsequent feature extraction. A stop word refers to a word in the system information that appears more than a preset threshold but has little practical meaning, such as me, he, etc.
终端在发布制度信息时，也可以预先标明制度信息的类别信息，以便服务器可以根据该类别信息，将制度信息纳入相应的目标信息树。若制度描述信息已包含制度信息的类别信息，可以根据类别信息将制度信息添加至相应的目标信息树。若制度描述信息并未包含制度信息的类别信息，则可以按照本申请提供的制度信息处理方法对制度信息进行分类管理。When issuing the system information, the terminal may also pre-specify the category information of the system information, so that the server can incorporate the system information into the corresponding target information tree according to the category information. If the system description information already contains category information of the system information, the system information can be added to the corresponding target information tree according to the category information. If the system description information does not include the category information of the system information, the system information may be classified and managed according to the system information processing method provided by the present application.
服务器分别获取原始词语集合中各个原始词语对应的同义词，将原始词语与对应的同义词形成扩展词语集合。每个原始词语都存在对应的扩展词语集合。同义词是指与原始词语含义相同或相近的词语，如原始词语为“不得”，同义词可为“切勿”、“禁止”、“避免”、“杜绝”等，将原始词语与对应的同义词形成扩展词语集合，如原始词语“不得”对应的扩展词语集合为{不得，切勿，禁止，避免，杜绝}。如原始词语集合为{a,b,c}，则原始词语集合中的每个原始词语都存在对应的扩展词语集合，如a对应的扩展词语集合为 {a,a1,a2}，b对应的扩展词语集合为{b,b1,b2,b3}，c对应的扩展词语集合为{c,c1,c2}。The server separately obtains the synonym corresponding to each original word in the original word set, and forms the extended word set by the original word and the corresponding synonym. There is a corresponding set of extended words for each original word. Synonyms refer to words that have the same or similar meaning as the original words. For example, the original words are “not allowed”, and the synonyms can be “no”, “forbidden”, “avoided”, “cancelled”, etc., and the original words and corresponding synonyms are formed. Expand the collection of words, such as the original words "not allowed" corresponding to the set of extended words as {no, no, prohibit, avoid, eliminate}. If the original word set is {a, b, c}, then each original word in the original word set has a corresponding extended word set, such as a corresponding extended word set of a is {a, a1, a2}, b corresponding The set of extended words is {b, b1, b2, b3}, and the set of extended words corresponding to c is {c, c1, c2}.
服务器按照与制度信息中各个原始词语出现的顺序，从各个原始词语对应的扩展词语集合中任意选择一个词语，按顺序形成一个扩展制度信息。当从扩展词语集合中选择不同的词语时，则形成不同的扩展制度信息，不同的扩展制度信息组成扩展制度信息集合。在其中一个实施例中，服务器对各个原始词语对应的扩展词语集合求笛卡尔积，形成由不同的扩展制度信息组成的扩展制度信息集合。两个集合X和Y的笛卡尔积，又称直积，表示为X×Y。第一个对象是X的成员而第二个对象是Y的所有可能有序对的其中一个成员。The server arbitrarily selects one word from the set of extended words corresponding to each original word according to the order in which the original words appear in the system information, and forms an extended system information in order. When different words are selected from the expanded word set, different extended system information is formed, and different extended system information constitutes an expanded system information set. In one of the embodiments, the server obtains a Cartesian product for the set of extended words corresponding to each original word, and forms a set of extended system information composed of different extended system information. The Cartesian product of the two sets X and Y, also known as the direct product, is expressed as X × Y. The first object is a member of X and the second object is one of all possible ordered pairs of Y.
制度管理模型用于根据输入从多个候选类型中确定与输入对应的目标类别。制度管理模型可以是通过逻辑回归算法、支持向量机算法等训练得到的模型。制度管理模型内部可以由多个子管理模型连接形成。由于已训练的制度管理模型的输入是经过扩展了的扩展制度信息集合，扩展后的各个扩展制度信息表达了与制度信息相同或相近的含义，提高了制度信息的有效覆盖范围，从而在后续输入已训练的制度管理模型后，可提高目标类别的精准性。The institutional management model is for determining a target category corresponding to the input from among a plurality of candidate types based on the input. The system management model can be a model obtained by training such as logistic regression algorithm and support vector machine algorithm. The system management model can be formed by multiple sub-management model connections. Since the input of the trained system management model is an expanded set of extended system information, the expanded information of each extended system expresses the same or similar meaning as the institutional information, and improves the effective coverage of the institutional information, so as to be input later. After the trained system management model, the accuracy of the target category can be improved.
服务器获取与目标类别对应的类别标注，筛选包含获取到的类别标注的一种或多种目标信息树。服务器根据制度描述信息生成信息节点，检测筛选得到的目标信息树中是否已存在相同的信息节点。若不存在，服务器将制度文件关联至该信息节点，将关联有制度文件的信息节点添加至筛选得到的目标信息树。The server obtains the category label corresponding to the target category, and filters one or more target information trees including the obtained category label. The server generates an information node according to the system description information, and detects whether the same information node already exists in the target information tree obtained by the screening. If not, the server associates the system file to the information node, and adds the information node associated with the system file to the filtered target information tree.
若筛选得到的目标信息树中已经存在相应的信息节点，则服务器只需将制度文件关联至已存在相应的信息节点。在另一个实施例中，服务器根据制度描述信息判断生成的信息节点与已存在的相同信息节点属于并列节点还是父子节点。当生成的信息节点与已存在的相同信息节点属于并列节点时，服务器对生成的信息节点与已存在的相同信息节点进行区别标记，将区别标记后的信息节点添加至相应的目标信息树，将制度文件关联至区别标记后的信息节点。If the corresponding information node already exists in the filtered target information tree, the server only needs to associate the system file to the corresponding information node. In another embodiment, the server determines, according to the system description information, whether the generated information node belongs to a parallel node or a parent child node with the same information node that already exists. When the generated information node and the existing information node belong to the parallel node, the server distinguishes the generated information node from the existing information node, and adds the marked information node to the corresponding target information tree. The system file is associated with the information node after the difference mark.
当生成的信息节点与已存在的相同信息节点属于并列节点时，服务器根据制度描述信息对生成的信息节点进行描述限定，即在制度描述信息中提取关键词，利用提取到的关键词对生成的信息节点进行语义扩充。例如，根据制度名称生成的信息节点为“公司福利管理制度”，在制度描述信息中提取关键词“研发部”，则语义扩充后的信息节点可以是“公司研发部福利管理制度”。服务器将语义扩充后的信息节点作为已存在的相同信息节点的子节点添加至相应的目标信息树，将制度文件关联至该子节点。When the generated information node and the existing same information node belong to the parallel node, the server describes and defines the generated information node according to the system description information, that is, extracts the keyword in the system description information, and generates the generated keyword pair. The information node performs semantic expansion. For example, the information node generated according to the name of the system is the “company welfare management system”, and the keyword “research and development department” is extracted from the system description information, and the information node after the semantic expansion may be the “company development department welfare management system”. The server adds the semantically expanded information node as a child node of the existing same information node to the corresponding target information tree, and associates the system file to the child node.
本实施例中，先形成每个原始词语对应的扩展词语集合，再通过扩展词语集合形成扩展制度信息集合，大大提高了扩展制度信息的扩展度，扩展后的各个扩展制度信息表达了与制度信息相同或相近的含义，提高了制度信息的有效覆盖范围，从而在后续输入已训练的制度管理模型后，可提高目标类别的精准性，进而可以准确将制度信息纳入相应的目标信息树，提高制度信息分类效率和准确率。In this embodiment, the extended word set corresponding to each original word is formed first, and then the expanded system information set is formed by expanding the word set, thereby greatly expanding the expansion degree of the extended system information, and the extended extended system information is expressed and institutional information. The same or similar meanings improve the effective coverage of institutional information, so that after the input of the trained system management model, the accuracy of the target category can be improved, and the system information can be accurately incorporated into the corresponding target information tree, and the system can be improved. Information classification efficiency and accuracy.
在其中一个实施例中，将多个文件片段推送至第一终端包括：当接收到制度学习请求时，随机生成密钥字符串；获取预存储的私钥，利用私钥对密钥字符串进行非对称加密，将加密后的密钥字符串发送至第一终端；当拆分得到文件片段时，定位制度子文件中的敏感字段，使用随机生成的密钥字符串对称加密敏感字段，生成文件片段对应的制度密文；将制度密文发送至第一终端；该方法还包括：获取第一终端在监控时段对制度密文操作的解密失败次数；根据解密失败次数，计算业务终端对应的信息泄漏风险值；当信息泄漏风险值超过阈值时，降低第一终端的制度查询权限。In one embodiment, pushing the plurality of file fragments to the first terminal comprises: randomly generating a key string when receiving the system learning request; acquiring a pre-stored private key, and using the private key to perform the key string Asymmetric encryption sends the encrypted key string to the first terminal; when splitting the file fragment, the sensitive field in the positioning system sub-file uses the randomly generated key string to symmetrically encrypt the sensitive field to generate a file. The system ciphertext corresponding to the fragment; the system ciphertext is sent to the first terminal; the method further includes: obtaining the number of decryption failures of the first terminal in the monitoring period for the ciphertext operation; and calculating the information corresponding to the service terminal according to the number of decryption failures Leakage risk value; when the information leakage risk value exceeds the threshold, the system query authority of the first terminal is lowered.
传统的数据加密方法包括对称加密和非对称加密。非对称加密安全性更好，但当传输的文件中涉及大量的敏感信息时，加密解密时间花费较长，速度慢。因此，非对称加密仅适合对少量数据进行加密，而对称加密需要在终端本地固定私钥，存在一定的安全风险，安全性不能保证。本实施例对对称加密和非对称加密进行有机结合，不仅能够对大量的敏感字段进行快速加密，也能使制度信息的传输和存储更加安全可靠。具体的，当接收到制度查询请求时，服务器按照设定的随机算法生成密钥字符串，并将生成的密钥字符串存储在内存中。在内存中存储密钥字符串时，还关联存储该密钥字符串的生成时间和对应的信息节点标识。举例来说，存储内容的格式可以是：信息节点A+生成时间+密钥字符串。Traditional data encryption methods include symmetric encryption and asymmetric encryption. Asymmetric encryption is more secure, but when a large amount of sensitive information is involved in the transmitted file, the encryption and decryption time takes a long time and is slow. Therefore, asymmetric encryption is only suitable for encrypting a small amount of data. Symmetric encryption requires a fixed private key at the terminal. There is a certain security risk, and security cannot be guaranteed. In this embodiment, the organic combination of symmetric encryption and asymmetric encryption can not only quickly encrypt a large number of sensitive fields, but also make the transmission and storage of system information more secure and reliable. Specifically, when receiving the system query request, the server generates a key string according to the set random algorithm, and stores the generated key string in the memory. When the key string is stored in the memory, the generation time of the key string and the corresponding information node identifier are also associated. For example, the format of the stored content may be: information node A + generation time + key string.
服务器使用预先存储的私钥非对称加密随机生成的密钥字符串，并将加密后的密钥字符串发送至第一终端。在其中一个实施例中，还可以在生成密钥字符串后，对密钥字符串进行内存存储前，即获取预存储的私钥对密钥字符串进行非对称加密，对加密后的密钥字符串进行存储。当查找到满足查询条件的制度子文件时，直接将存储的加密后的密钥字符串发送至第一终端，以避免拖慢请求的效率。The server asymmetrically encrypts the randomly generated key string using the pre-stored private key, and sends the encrypted key string to the first terminal. In one embodiment, after the key string is generated, the key string is stored in the memory, that is, the pre-stored private key is obtained to asymmetrically encrypt the key string, and the encrypted key is obtained. Strings are stored. When the system sub-file satisfying the query condition is found, the stored encrypted key string is directly sent to the first terminal to avoid slowing down the request.
服务器对查找到的制度子文件进行解析得到文件内容，按照设定的敏感信息查找规则查找制度子文件中所包含的敏感信息以定位敏感信息对应的敏感字段，并使用随机生成的密钥字符串(未经预设私钥非对称加密的密钥字符串)对定位的敏感字段进行对称加密，生成制度密文。生成的制度密文中仅敏感字段以加密后形成的字符串进行隐秘显示，其他内容均以原始明文的形式显示。在其中一个实施例中，还可以预先对制度子文件中的敏感信息进行标记，如文字加粗或者以不同的颜色突出显示敏感信息等。在定位文件中的敏感字段时，只需查找标记位置即可。对敏感字段进行加密后，可去除敏感字段的标记也可以不去除，具体可根据需要进行配置。The server parses the found system sub-file to obtain the file content, searches the sensitive information contained in the system sub-file according to the set sensitive information search rule to locate the sensitive field corresponding to the sensitive information, and uses the randomly generated key string. (A key string that is asymmetrically encrypted without a preset private key) symmetrically encrypts the located sensitive field to generate a system ciphertext. Only sensitive fields in the generated system ciphertext are displayed in secret by the encrypted string, and other contents are displayed in the original plaintext. In one of the embodiments, sensitive information in the system sub-file may also be marked in advance, such as text bolding or highlighting sensitive information in different colors. When locating sensitive fields in a file, just look up the tag location. After the sensitive field is encrypted, the mark of the sensitive field can be removed or removed, and the configuration can be configured as needed.
服务器将生成制度密文返回至第一终端，以使相应用户在第一终端进行制度学习。当第一终端需要对制度密文进行相应的数据处理时，可通过从服务器获取的加密后的密钥字符串对制度密文进行解密以获取原始明文文件。具体的，第一终端使用服务器预先公布的公钥对加密的密钥字符串进行解密，得到密钥字符串；再使用密钥字符串对制度密文中的敏感字段进行解密。需要说明的是，非对称加密采用的公钥私钥对随机动态生成，定期更新。The server returns the generated system ciphertext to the first terminal, so that the corresponding user performs system learning at the first terminal. When the first terminal needs to perform corresponding data processing on the system ciphertext, the system ciphertext can be decrypted by the encrypted key string obtained from the server to obtain the original plaintext file. Specifically, the first terminal decrypts the encrypted key string by using a public key pre-published by the server to obtain a key string; and then decrypts the sensitive field in the system ciphertext by using the key string. It should be noted that the public key private key pair used by asymmetric encryption is dynamically generated and updated periodically.
服务器获取第一终端在监控时段对制度密文操作生成的操作行为日志。操作行为日 志是指通过监控用户作用于业务终端的操作事件所形成的日志。其中，操作事件可以包括制度查询操作，以及对制度密文的下载操作、解密操作或转发操作等。服务器按照预设时间频率在多个业务终端分别提取相应用户的操作行为日志。The server obtains an operation behavior log generated by the first terminal during the monitoring period on the system ciphertext operation. The operational behavior log refers to a log formed by monitoring operational events of the user acting on the service terminal. The operation event may include an system query operation, a download operation, a decryption operation, or a forwarding operation on the system ciphertext. The server extracts the operation behavior log of the corresponding user in multiple service terminals according to the preset time frequency.
服务器根据操作行为日志，计算业务终端对应的信息泄漏风险值。具体的，服务器对提取到的操作行为日志进行解析，得到对应的操作行为数据。操作行为数据包括对制度密文的下载失败次数、解密失败次数或转发失败次数等。服务器根据对制度密文的下载失败次数、解密失败次数和转发失败次数，计算业务终端对应的信息泄漏风险值。The server calculates the information leakage risk value corresponding to the service terminal according to the operation behavior log. Specifically, the server parses the extracted operation behavior log to obtain corresponding operation behavior data. The operational behavior data includes the number of download failures of the system ciphertext, the number of decryption failures, or the number of failed forwardings. The server calculates the information leakage risk value corresponding to the service terminal according to the number of download failures, the number of decryption failures, and the number of failed forwardings of the system ciphertext.
服务器监测信息泄露风险值超过阈值。当信息泄漏风险值超过阈值时，服务器根据超过阈值的信息泄露风险值及对应的用户标识生成信息泄漏预警。信息泄漏预警有多种实施方式，其中一种实施方式为服务器根据用户标识以及相应的信息泄露风险值生成用户行为监控报表，在用户行为监控报表中将超过阈值的信息泄露风险值及对应的用户标识进行区别标记。服务器将信息泄露预警发送至监控终端，以提示监控终端即使采取信息防泄漏措施，如降低相应用户对业务***的操作权限等。监控终端为预先指定的具有监控权限的终端。容易理解，监控终端可以包括用户终端，以直接对相应用户进行提示。The server monitors the information leakage risk value to exceed the threshold. When the information leakage risk value exceeds the threshold, the server generates an information leakage warning according to the information leakage risk value exceeding the threshold and the corresponding user identifier. The information leakage warning has multiple implementation modes. One implementation manner is that the server generates a user behavior monitoring report according to the user identifier and the corresponding information leakage risk value, and the information leakage risk value exceeding the threshold value and the corresponding user are displayed in the user behavior monitoring report. The logo is marked differently. The server sends an information leakage warning to the monitoring terminal, so as to prompt the monitoring terminal to take information leakage prevention measures, such as reducing the operation authority of the corresponding user to the business system. The monitoring terminal is a pre-designated terminal with monitoring authority. It is easy to understand that the monitoring terminal can include a user terminal to directly prompt the corresponding user.
本实施例中，由于密钥字符串采用的是非对称加密，有效保证了密钥字符串的安全性，且仅针对数据量较小的密钥字符串进行非对称加解密，不会影响加解密效率。对敏感字段采用的是对称加解密，即使隐私字段数量庞大，也能够快速加解密，伴随随机动态的密钥生成方式，可以即保证了加解密效率又有效地保障了信息的安全。此外，第一终端对制度密文进行解密学习时，根据第一终端在监控时段对制度密文操作生成的操作行为日志，可以计算业务终端对应的信息泄漏风险值；当信息泄漏风险值超过阈值时，可以及时降低业务终端的制度查询权限，进一步提高信息安全性。In this embodiment, since the key string is asymmetrically encrypted, the security of the key string is effectively ensured, and only asymmetrically encrypting and decrypting the key string with a small amount of data does not affect encryption and decryption. effectiveness. Symmetric encryption and decryption is adopted for sensitive fields. Even if the number of privacy fields is large, it can be quickly encrypted and decrypted. With the random dynamic key generation method, the encryption and decryption efficiency can be ensured and the information security can be effectively guaranteed. In addition, when the first terminal decrypts the system ciphertext, according to the operation behavior log generated by the first terminal in the monitoring period for the system ciphertext operation, the information leakage risk value corresponding to the service terminal can be calculated; when the information leakage risk value exceeds the threshold In time, the system query authority of the service terminal can be reduced in time to further improve information security.
在其中一个实施例中，文件片段包括文档片段；学习事件包括文档关闭事件；捕获第一终端发生的对文件片段的学习事件，获取学习事件对应的制度学习数据包括：捕获第一终端发生的对文档片段的实际阅读时间；获取文档片段的数据量，根据数据量计算文档片段对应的常规阅读时间；当捕获到文档关闭事件时，记录文档片段的阅读位置，根据文档片段生成随机测评问卷，将随机测评问卷发送至第一终端；接收第一终端在预设时长内返回的随机测评问卷的答案信息，对答案信息进行打分，得到测评分值；根据测评分值、实际阅读时间以及常规阅读时间，计算第一终端对应的有效学习时间。In one embodiment, the file segment includes a document fragment; the learning event includes a document closing event; capturing a learning event for the file segment that occurs at the first terminal, and acquiring the institutional learning data corresponding to the learning event includes: capturing a pair generated by the first terminal The actual reading time of the document fragment; the data volume of the document fragment is obtained, and the normal reading time corresponding to the document fragment is calculated according to the data amount; when the document closing event is captured, the reading position of the document fragment is recorded, and a random evaluation questionnaire is generated according to the document fragment, The random evaluation questionnaire is sent to the first terminal; the answer information of the random evaluation questionnaire returned by the first terminal within the preset duration is received, the answer information is scored, and the score value is obtained; according to the measured score value, the actual reading time, and the regular reading time. And calculating an effective learning time corresponding to the first terminal.
根据制度子文件的文件类型不同，拆分得到的文件片段可以是文档片段，视频片段等。对于不同数据量的文档片段，对应的常规阅读时间不同。对于不同数据量的视频片段，对应的常规观看时间不同。视频片段具有对应的播放时间，常规观看时间为短于播放时间的时间长度。According to the file type of the system sub-file, the fragment obtained can be a document fragment, a video clip, and the like. For document fragments of different data volumes, the corresponding regular reading time is different. For video clips of different data volumes, the corresponding regular viewing time is different. The video clip has a corresponding play time, and the regular viewing time is a length of time shorter than the play time.
当拆分得到的文件片段为文档片段时，服务器捕获第一终端发生的对文档片段的学习事件，获取学习事件对应的制度学习数据。制度学习数据包括对文档片段的实际阅读时间。服务器计算文档片段的数据量，根据该数据量计算文档片段对应的常规阅读时间。学习事 件包括文档关闭事件。当捕获到文档关闭事件时，服务器记录文档片段的阅读位置，便于用户进行下一次制度学习。When the split file segment is a document segment, the server captures a learning event for the document segment that occurs at the first terminal, and acquires system learning data corresponding to the learning event. Institutional learning data includes the actual reading time of a document fragment. The server calculates the data amount of the document segment, and calculates the regular reading time corresponding to the document segment according to the data amount. Learning events include document close events. When the document close event is captured, the server records the reading position of the document fragment, which is convenient for the user to learn the next system.
在另一个实施例中，服务器根据文档片段生成随机测评问卷，将随机测评问卷发送至第一终端。测评问卷包括多个随机问题。服务器接收第一终端在预设时长内返回的随机问题的答案信息，对答案信息进行打分，得到测评分值。服务器计算实际阅读时间与常规阅读时间的时间偏差。服务器根据测评分值和时间偏差以及预设的分别对应的权重因子，综合计算第一终端对应的有效学习时间，使得有效学习时间的测算更加精准。In another embodiment, the server generates a random assessment questionnaire based on the document fragments and transmits the random assessment questionnaire to the first terminal. The assessment questionnaire included multiple random questions. The server receives the answer information of the random question returned by the first terminal within the preset duration, and scores the answer information to obtain a score value. The server calculates the time deviation between the actual reading time and the regular reading time. The server comprehensively calculates the effective learning time corresponding to the first terminal according to the measured score value and the time deviation and the preset corresponding weight factors, so that the effective learning time is more accurate.
本实施例中，根据实际阅读时间与常规阅读时间的时间偏差，可以判断用户在制度学习过程是否作弊；通过对随机问题的答案信息进行打分，可以判断用户进行制度学习的效果；根据测评分值和时间偏差两个维度的信息计算用户的有效学习时间，使得有效学习时间的测算更加贴合实际，也更加精准。In this embodiment, according to the time deviation between the actual reading time and the regular reading time, it can be determined whether the user is cheating in the system learning process; by scoring the answer information of the random question, the effect of the user learning the system can be judged; The two dimensions of information and time deviation calculate the effective learning time of the user, making the measurement of the effective learning time more realistic and more accurate.
应该理解的是，虽然图2和图3的流程图中的各个步骤按照箭头的指示依次显示，但是这些步骤并不是必然按照箭头指示的顺序依次执行。除非本文中有明确的说明，这些步骤的执行并没有严格的顺序限制，这些步骤可以以其它的顺序执行。而且，图2和图3中的至少一部分步骤可以包括多个子步骤或者多个阶段，这些子步骤或者阶段并不必然是在同一时刻执行完成，而是可以在不同的时刻执行，这些子步骤或者阶段的执行顺序也不必然是依次进行，而是可以与其它步骤或者其它步骤的子步骤或者阶段的至少一部分轮流或者交替地执行。It should be understood that although the various steps in the flowcharts of FIGS. 2 and 3 are sequentially displayed in accordance with the indication of the arrows, these steps are not necessarily performed in the order indicated by the arrows. Except as explicitly stated herein, the execution of these steps is not strictly limited, and the steps may be performed in other orders. Moreover, at least some of the steps in FIGS. 2 and 3 may include a plurality of sub-steps or stages, which are not necessarily performed at the same time, but may be performed at different times, or The order of execution of the stages is also not necessarily sequential, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.
在其中一个实施例中，如图6所示，提供了一种制度信息处理装置，包括：制度查询模块602、制度拆分模块604和学习监控模块606，其中：In one embodiment, as shown in FIG. 6, an institutional information processing apparatus is provided, including: an system query module 602, a system splitting module 604, and a learning monitoring module 606, wherein:
制度查询模块602，用于接收第一终端发送的制度学习请求，制度学习请求携带了适用对象标识和查询条件；获取适用对象标识对应的关联信息树；关联信息树包括多个信息节点及每个信息节点关联的多个制度子文件；在关联信息树中查找满足查询条件的信息节点。The system query module 602 is configured to receive an institutional learning request sent by the first terminal, where the system learning request carries the applicable object identifier and the query condition, and acquires an associated information tree corresponding to the applicable object identifier; the associated information tree includes multiple information nodes and each Multiple system sub-files associated with the information node; find information nodes that satisfy the query conditions in the associated information tree.
制度拆分模块604，用于获取查找到的信息节点对应的制度子文件，将制度子文件拆分为多个文件片段，将多个文件片段推送至第一终端。The system splitting module 604 is configured to obtain a system sub-file corresponding to the found information node, split the system sub-file into a plurality of file segments, and push the plurality of file segments to the first terminal.
学习监控模块606，用于捕获第一终端发生的对文件片段的学习事件，获取学习事件对应的制度学习数据；制度学习数据包括有效学习时间；当有效学习时间达到阈值时，获取目标资源，将目标资源转移至第一终端。The learning monitoring module 606 is configured to capture a learning event of a file segment generated by the first terminal, and acquire system learning data corresponding to the learning event; the system learning data includes an effective learning time; when the effective learning time reaches a threshold, the target resource is acquired, and The target resource is transferred to the first terminal.
在其中一个实施例中，该装置还包括信息归档模块608，用于监测第二终端发布的制度信息；制度信息包括制度描述信息及关联的制度文件；制度文件包括多个制度条款以及每个制度条款对应的适用对象标识；对制度信息进行分类，根据分类结果将制度信息添加至预设的一个或多个目标信息树；获取目标信息树对应的多个关联信息树；每个关联信息树具有对应的适用对象标识；对制度文件进行拆分，利用每个适用对象标识对应的制度条 款生成相应适用对象标识对应的制度子文件；将每个适用对象标识对应的制度描述信息和制度子文件添加至相应的关联信息树。In one embodiment, the apparatus further includes an information archiving module 608 for monitoring system information issued by the second terminal; the system information includes system description information and associated system files; the system file includes multiple system terms and each system The applicable object identifier corresponding to the clause; classifying the system information, adding the system information to the preset one or more target information trees according to the classification result; acquiring a plurality of associated information trees corresponding to the target information tree; each associated information tree has Corresponding applicable object identifier; split the system file, use the system clause corresponding to each applicable object identifier to generate the system sub-file corresponding to the applicable object identifier; add the system description information and the system sub-file corresponding to each applicable object identifier To the corresponding associated information tree.
在其中一个实施例中，信息归档模块608还用于对制度信息进行分词得到对应的原始词语集合；原始词语集合包括多个原始词语；对各个原始词语进行同义扩展，生成每个原始词语对应的扩展词语集合；根据各个扩展词语集合形成制度信息对应的扩展制度信息集合；将扩展制度信息集合输入预设的制度管理模型，得到制度信息对应的目标类别；获取多个目标信息树分别对应的类别标注，筛选包含与目标类别对应类别标注的目标信息树，将制度信息添加至筛选得到的目标信息树。In one embodiment, the information archiving module 608 is further configured to perform word segmentation on the system information to obtain a corresponding original word set; the original word set includes a plurality of original words; synonymously expand each original word to generate each original word corresponding a set of extended words; forming a set of extended system information corresponding to the system information according to each set of extended words; inputting the expanded system information set into a preset institutional management model, obtaining a target category corresponding to the institutional information; acquiring a plurality of target information trees respectively corresponding The category labeling screen filters the target information tree including the category label corresponding to the target category, and adds the system information to the filtered target information tree.
在其中一个实施例中，制度拆分模块604还用于当接收到制度学习请求时，随机生成密钥字符串；获取预存储的私钥，利用私钥对密钥字符串进行非对称加密，将加密后的密钥字符串发送至第一终端；当拆分得到文件片段时，定位制度子文件中的敏感字段，使用随机生成的密钥字符串对称加密敏感字段，生成文件片段对应的制度密文；将制度密文发送至第一终端；学习监控模块606还用于获取第一终端在监控时段对制度密文操作的解密失败次数；根据解密失败次数，计算业务终端对应的信息泄漏风险值；当信息泄漏风险值超过阈值时，降低第一终端的制度查询权限。In one embodiment, the system splitting module 604 is further configured to randomly generate a key string when receiving the system learning request; obtain a pre-stored private key, and asymmetrically encrypt the key string by using a private key, Sending the encrypted key string to the first terminal; when splitting the obtained file fragment, the sensitive field in the positioning system subfile uses a randomly generated key string to symmetrically encrypt the sensitive field, and generates a system corresponding to the file fragment. The ciphertext is sent to the first terminal; the learning monitoring module 606 is further configured to obtain the number of decryption failures of the first terminal in the monitoring period for the ciphertext operation; and calculate the information leakage risk corresponding to the service terminal according to the number of decryption failures Value; when the information leakage risk value exceeds the threshold, the system query authority of the first terminal is lowered.
在其中一个实施例中，制度拆分模块604还用于获取制度子文件的文件类型；根据文件类型，获取对应的数据量阈值；根据数据量阈值对制度子文件进行拆分，得到多个文件片段；根据拆分顺序，将多个文件片段依次推送至第一终端。In one embodiment, the system splitting module 604 is further configured to obtain a file type of the system sub-file; obtain a corresponding data amount threshold according to the file type; and split the system sub-file according to the data quantity threshold to obtain multiple files. Fragment; according to the splitting order, multiple file segments are sequentially pushed to the first terminal.
在其中一个实施例中，文件片段包括文档片段；学习事件包括文档关闭事件；学习监控模块606还用于捕获第一终端发生的对文档片段的实际阅读时间；获取文档片段的数据量，根据数据量计算文档片段对应的常规阅读时间；当捕获到文档关闭事件时，记录文档片段的阅读位置，根据文档片段生成随机测评问卷，将随机测评问卷发送至第一终端；接收第一终端在预设时长内返回的随机测评问卷的答案信息，对答案信息进行打分，得到测评分值；根据测评分值、实际阅读时间以及常规阅读时间，计算第一终端对应的有效学习时间。In one embodiment, the file fragment includes a document fragment; the learning event includes a document close event; the learning monitoring module 606 is further configured to capture an actual reading time of the document fragment generated by the first terminal; and obtain a data amount of the document fragment according to the data. Calculating the normal reading time corresponding to the document segment; when the document closing event is captured, recording the reading position of the document segment, generating a random evaluation questionnaire according to the document segment, and transmitting the random evaluation questionnaire to the first terminal; receiving the first terminal is preset The answer information of the random evaluation questionnaire returned within the duration, the answer information is scored, and the score value is obtained; and the effective learning time corresponding to the first terminal is calculated according to the measured score value, the actual reading time, and the regular reading time.
在其中一个实施例中，学习监控模块606还用于当有效学习时间达到阈值时，向第一终端发送资源抽取页面；监测第一终端在资源抽取页面发生的资源抽取操作，根据资源抽取操作，获取随机份额的目标资源；将获取到的目标资源转移至第一终端。In one embodiment, the learning monitoring module 606 is further configured to: when the effective learning time reaches the threshold, send a resource extraction page to the first terminal; and monitor a resource extraction operation that occurs by the first terminal on the resource extraction page, according to the resource extraction operation, Obtain a target resource of a random share; transfer the obtained target resource to the first terminal.
关于制度信息处理装置的具体限定可以参见上文中对于制度信息处理方法的限定，在此不再赘述。上述制度信息处理装置中的各个模块可全部或部分通过软件、硬件及其组合来实现。上述各模块可以硬件形式内嵌于或独立于计算机设备中的处理器中，也可以以软件形式存储于计算机设备中的存储器中，以便于处理器调用执行以上各个模块对应的操作。For the specific definition of the system information processing device, reference may be made to the above limitation of the system information processing method, and details are not described herein again. Each of the above-described system information processing apparatuses may be implemented in whole or in part by software, hardware, and a combination thereof. Each of the above modules may be embedded in or independent of the processor in the computer device, or may be stored in a memory in the computer device in a software form, so that the processor invokes the operations corresponding to the above modules.
在其中一个实施例中，提供了一种计算机设备，该计算机设备可以是服务器，其内部 结构图可以如图6所示。该计算机设备包括通过***总线连接的处理器、存储器、网络接口和数据库。其中，该计算机设备的处理器用于提供计算和控制能力。该计算机设备的存储器包括非易失性存储介质、内存储器。该非易失性存储介质存储有操作***、计算机可读指令和数据库。该内存储器为非易失性存储介质中的操作***和计算机可读指令的运行提供环境。该计算机设备的数据库用于存储制度信息。该计算机设备的网络接口用于与外部的终端通过网络连接通信。该计算机可读指令被处理器执行时实现本申请任意一个实施例中提供的制度信息处理方法的步骤。In one of the embodiments, a computer device is provided, which may be a server, the internal structure of which may be as shown in FIG. The computer device includes a processor, memory, network interface, and database connected by a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium, an internal memory. The non-volatile storage medium stores an operating system, computer readable instructions, and a database. The internal memory provides an environment for operation of an operating system and computer readable instructions in a non-volatile storage medium. The database of the computer device is used to store institutional information. The network interface of the computer device is used to communicate with an external terminal via a network connection. The steps of the system information processing method provided in any one of the embodiments of the present application when the computer readable instructions are executed by the processor.
本领域技术人员可以理解，图6中示出的结构，仅仅是与本申请方案相关的部分结构的框图，并不构成对本申请方案所应用于其上的计算机设备的限定，具体的计算机设备可以包括比图中所示更多或更少的部件，或者组合某些部件，或者具有不同的部件布置。It will be understood by those skilled in the art that the structure shown in FIG. 6 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation of the computer device to which the solution of the present application is applied. The specific computer device may It includes more or fewer components than those shown in the figures, or some components are combined, or have different component arrangements.
一个或多个存储有计算机可读指令的非易失性存储介质，计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器实现本申请任意一个实施例中提供的制度信息处理方法的步骤。One or more non-volatile storage media storing computer readable instructions, when executed by one or more processors, causing one or more processors to implement a system as provided in any one embodiment of the present application The steps of the information processing method.
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机可读指令来指令相关的硬件来完成，计算机可读指令可存储于一非易失性计算机可读取存储介质中，该计算机可读指令在执行时，可包括如上述各方法的实施例的流程。其中，本申请所提供的各实施例中所使用的对存储器、存储、数据库或其它介质的任何引用，均可包括非易失性和/或易失性存储器。非易失性存储器可包括只读存储器(ROM)、可编程ROM(PROM)、电可编程ROM(EPROM)、电可擦除可编程ROM(EEPROM)或闪存。易失性存储器可包括随机存取存储器(RAM)或者外部高速缓冲存储器。作为说明而非局限，RAM以多种形式可得，诸如静态RAM(SRAM)、动态RAM(DRAM)、同步DRAM(SDRAM)、双数据率SDRAM(DDRSDRAM)、增强型SDRAM(ESDRAM)、同步链路(Synchlink)DRAM(SLDRAM)、存储器总线(Rambus)直接RAM(RDRAM)、直接存储器总线动态RAM(DRDRAM)、以及存储器总线动态RAM(RDRAM)等。A person skilled in the art can understand that all or part of the process of implementing the above embodiment method can be completed by computer-readable instructions for instructing related hardware, and the computer readable instructions can be stored in a non-volatile computer readable. In the storage medium, the computer readable instructions, when executed, may include the flow of an embodiment of the methods as described above. Any reference to a memory, storage, database or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile memory can include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of formats, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronization chain. Synchlink DRAM (SLDRAM), Memory Bus (Rambus) Direct RAM (RDRAM), Direct Memory Bus Dynamic RAM (DRDRAM), and Memory Bus Dynamic RAM (RDRAM).
以上实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。The technical features of the above embodiments may be arbitrarily combined. For the sake of brevity of description, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, It is considered to be the range described in this specification.
以上实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请专利的保护范围应以所附权利要求为准。The above embodiments are merely illustrative of several embodiments of the present application, and the description thereof is more specific and detailed, but is not to be construed as limiting the scope of the invention. It should be noted that a number of variations and modifications may be made by those skilled in the art without departing from the spirit and scope of the present application. Therefore, the scope of the invention should be determined by the appended claims.

Claims (20)

  1. 一种制度信息处理方法，包括：A system information processing method, comprising:
    接收第一终端发送的制度学习请求，所述制度学习请求携带了适用对象标识和查询条件；Receiving an institutional learning request sent by the first terminal, where the system learning request carries an applicable object identifier and a query condition;
    获取所述适用对象标识对应的关联信息树；所述关联信息树包括多个信息节点及每个所述信息节点关联的多个制度子文件；Obtaining an association information tree corresponding to the applicable object identifier; the association information tree includes a plurality of information nodes and a plurality of system sub-files associated with each of the information nodes;
    在所述关联信息树中查找满足所述查询条件的信息节点；Finding an information node that satisfies the query condition in the association information tree;
    获取查找到的信息节点对应的制度子文件，将所述制度子文件拆分为多个文件片段，将多个所述文件片段推送至所述第一终端；Obtaining a system sub-file corresponding to the found information node, splitting the system sub-file into a plurality of file segments, and pushing a plurality of the file segments to the first terminal;
    捕获所述第一终端发生的对所述文件片段的学习事件，获取所述学习事件对应的制度学习数据；所述制度学习数据包括有效学习时间；及Capturing a learning event of the file segment that occurs in the first terminal, acquiring system learning data corresponding to the learning event; and the system learning data includes an effective learning time;
    当所述有效学习时间达到阈值时，获取目标资源，将所述目标资源转移至所述第一终端。When the valid learning time reaches the threshold, the target resource is acquired, and the target resource is transferred to the first terminal.
  2. 根据权利要求1所述的方法，其特征在于，在获取所述适用对象标识对应的关联信息树之前，所述方法还包括：The method according to claim 1, wherein the method further comprises: before acquiring the associated information tree corresponding to the applicable object identifier, the method further comprising:
    监测第二终端发布的制度信息；所述制度信息包括制度描述信息及关联的制度文件；所述制度文件包括多个制度条款以及每个制度条款对应的适用对象标识；Monitoring system information issued by the second terminal; the system information includes system description information and associated system documents; the system file includes a plurality of system clauses and an applicable object identifier corresponding to each system clause;
    对所述制度信息进行分类，根据分类结果将所述制度信息添加至预设的一个或多个目标信息树；Classifying the system information, and adding the system information to a preset one or more target information trees according to the classification result;
    获取所述目标信息树对应的多个关联信息树；每个所述关联信息树具有对应的适用对象标识；Acquiring a plurality of association information trees corresponding to the target information tree; each of the association information trees has a corresponding applicable object identifier;
    对所述制度文件进行拆分，利用每个适用对象标识对应的制度条款生成相应适用对象标识对应的制度子文件；及Separating the system files, and using the system terms corresponding to each applicable object identifier to generate a system sub-file corresponding to the applicable object identifier; and
    将每个所述适用对象标识对应的制度描述信息和制度子文件添加至相应的关联信息树。The system description information and the system sub-file corresponding to each of the applicable object identifiers are added to the corresponding association information tree.
  3. 根据权利要求2所述的方法，其特征在于，对所述制度信息进行分类，根据分类结果将所述制度信息添加至预设的一个或多个目标信息树，包括：The method according to claim 2, wherein the system information is classified, and the system information is added to the preset one or more target information trees according to the classification result, including:
    对所述制度信息进行分词得到对应的原始词语集合；所述原始词语集合包括多个原始词语；Performing word segmentation on the system information to obtain a corresponding original word set; the original word set includes a plurality of original words;
    对各个原始词语进行同义扩展，生成每个原始词语对应的扩展词语集合；Synchronous expansion of each original word to generate a set of extended words corresponding to each original word;
    根据各个扩展词语集合形成所述制度信息对应的扩展制度信息集合；Forming an extended system information set corresponding to the system information according to each set of extended words;
    将所述扩展制度信息集合输入预设的制度管理模型，得到所述制度信息对应的目标类别；及Inputting the extended system information set into a preset system management model to obtain a target category corresponding to the system information; and
    获取多个所述目标信息树分别对应的类别标注，筛选包含与所述目标类别对应类别标注的目标信息树，将所述制度信息添加至筛选得到的目标信息树。Obtaining a category label corresponding to each of the plurality of target information trees, filtering a target information tree including a category label corresponding to the target category, and adding the system information to the filtered target information tree.
  4. 根据权利要求1所述的方法，其特征在于，将多个所述文件片段推送至所述第一终端，包括：The method of claim 1, wherein the pushing the plurality of the file fragments to the first terminal comprises:
    当接收到所述制度学习请求时，随机生成密钥字符串；When the system learning request is received, a key string is randomly generated;
    获取预存储的私钥，利用所述私钥对所述密钥字符串进行非对称加密，将加密后的所述密钥字符串发送至所述第一终端；Obtaining a pre-stored private key, performing asymmetric encryption on the key string by using the private key, and sending the encrypted key string to the first terminal;
    当拆分得到所述文件片段时，定位所述制度子文件中的敏感字段，使用随机生成的密钥字符串对称加密所述敏感字段，生成文件片段对应的制度密文；When the file fragment is obtained by splitting, the sensitive field in the system sub-file is located, and the sensitive field is symmetrically encrypted using a randomly generated key string to generate an institutional ciphertext corresponding to the file fragment;
    将所述制度密文发送至所述第一终端；所述方法还包括：Sending the system ciphertext to the first terminal; the method further includes:
    获取所述第一终端在监控时段对所述制度密文操作的解密失败次数；Acquiring the number of times the first terminal decrypts the system ciphertext operation during the monitoring period;
    根据所述解密失败次数，计算所述业务终端对应的信息泄漏风险值；及Calculating an information leakage risk value corresponding to the service terminal according to the number of decryption failures; and
    当所述信息泄漏风险值超过阈值时，降低所述第一终端的制度查询权限。When the information leakage risk value exceeds a threshold, the system query authority of the first terminal is lowered.
  5. 根据权利要求1所述的方法，其特征在于，将所述制度子文件拆分为多个文件片段，将多个所述文件片段推送至所述第一终端，包括：The method according to claim 1, wherein the splitting the system sub-file into a plurality of file segments and pushing the plurality of the file segments to the first terminal comprises:
    获取所述制度子文件的文件类型；Obtaining the file type of the system sub-file;
    根据所述文件类型，获取对应的数据量阈值；Obtaining a corresponding data amount threshold according to the file type;
    根据所述数据量阈值对所述制度子文件进行拆分，得到多个文件片段；及Splitting the system sub-file according to the data amount threshold to obtain a plurality of file segments; and
    根据拆分顺序，将多个所述文件片段依次推送至所述第一终端。A plurality of the file segments are sequentially pushed to the first terminal according to a splitting order.
  6. 根据权利要求1所述的方法，其特征在于，所述文件片段包括文档片段；所述学习事件包括文档关闭事件；捕获所述第一终端发生的对所述文件片段的学习事件，获取所述学习事件对应的制度学习数据，包括：The method of claim 1, wherein the file segment comprises a document fragment; the learning event comprises a document close event; capturing a learning event for the file segment that occurs at the first terminal, obtaining the Institutional learning data corresponding to learning events, including:
    捕获所述第一终端发生的对所述文档片段的实际阅读时间；Capturing an actual reading time of the document segment that occurs by the first terminal;
    获取所述文档片段的数据量，根据所述数据量计算所述文档片段对应的常规阅读时间；Obtaining an amount of data of the document segment, and calculating a regular reading time corresponding to the document segment according to the data amount;
    当捕获到所述文档关闭事件时，记录所述文档片段的阅读位置，根据所述文档片段生成随机测评问卷，将所述随机测评问卷发送至所述第一终端；Recording a reading position of the document segment when the document closing event is captured, generating a random evaluation questionnaire according to the document segment, and transmitting the random evaluation questionnaire to the first terminal;
    接收所述第一终端在预设时长内返回的所述随机测评问卷的答案信息，对所述答案信息进行打分，得到测评分值；及Receiving the answer information of the random evaluation questionnaire returned by the first terminal within a preset duration, and scoring the answer information to obtain a score value; and
    根据所述测评分值、所述实际阅读时间以及所述常规阅读时间，计算所述第一终端对应的有效学习时间。Calculating an effective learning time corresponding to the first terminal according to the measured score value, the actual reading time, and the regular reading time.
  7. 根据权利要求1所述的方法，其特征在于，当所述有效学习时间达到阈值时，获取目标资源，将所述目标资源转移至所述第一终端，包括：The method according to claim 1, wherein when the effective learning time reaches a threshold, acquiring a target resource and transferring the target resource to the first terminal comprises:
    当所述有效学习时间达到阈值时，向所述第一终端发送资源抽取页面；Sending a resource extraction page to the first terminal when the effective learning time reaches a threshold;
    监测所述第一终端在所述资源抽取页面发生的资源抽取操作，根据所述资源抽取操作，获取随机份额的目标资源；及Monitoring a resource extraction operation performed by the first terminal on the resource extraction page, and acquiring a target resource of a random share according to the resource extraction operation; and
    将获取到的目标资源转移至所述第一终端。Transfer the acquired target resource to the first terminal.
  8. 一种制度信息处理装置，包括：An institutional information processing device comprising:
    制度查询模块，用于接收第一终端发送的制度学习请求，所述制度学习请求携带了适用对象标识和查询条件；获取所述适用对象标识对应的关联信息树；所述关联信息树包括多个信息节点及每个所述信息节点关联的多个制度子文件；在所述关联信息树中查找满足所述查询条件的信息节点；The system query module is configured to receive the system learning request sent by the first terminal, where the system learning request carries the applicable object identifier and the query condition; and the associated information tree corresponding to the applicable object identifier is obtained; the associated information tree includes multiple An information node and a plurality of system sub-files associated with each of the information nodes; and searching for, in the associated information tree, an information node that satisfies the query condition;
    制度拆分模块，用于获取查找到的信息节点对应的制度子文件，将所述制度子文件拆分为多个文件片段，将多个所述文件片段推送至所述第一终端；及a system splitting module, configured to obtain a system sub-file corresponding to the found information node, split the system sub-file into a plurality of file segments, and push the plurality of the file segments to the first terminal; and
    学习监控模块，用于捕获所述第一终端发生的对所述文件片段的学习事件，获取所述学习事件对应的制度学习数据；所述制度学习数据包括有效学习时间；当有效学习时间达到阈值时，获取目标资源，将目标资源转移至所述第一终端。a learning monitoring module, configured to capture a learning event of the file segment generated by the first terminal, and acquire institutional learning data corresponding to the learning event; the system learning data includes an effective learning time; when the effective learning time reaches a threshold And acquiring the target resource, and transferring the target resource to the first terminal.
  9. 一种计算机设备，包括存储器及一个或多个处理器，所述存储器中储存有计算机可读指令，所述计算机可读指令被所述一个或多个处理器执行时，使得所述一个或多个处理器执行以下步骤：A computer device comprising a memory and one or more processors having stored therein computer readable instructions, the computer readable instructions being executed by the one or more processors to cause the one or more The processors perform the following steps:
    接收第一终端发送的制度学习请求，所述制度学习请求携带了适用对象标识和查询条件；Receiving an institutional learning request sent by the first terminal, where the system learning request carries an applicable object identifier and a query condition;
    获取所述适用对象标识对应的关联信息树；所述关联信息树包括多个信息节点及每个所述信息节点关联的多个制度子文件；Obtaining an association information tree corresponding to the applicable object identifier; the association information tree includes a plurality of information nodes and a plurality of system sub-files associated with each of the information nodes;
    在所述关联信息树中查找满足所述查询条件的信息节点；Finding an information node that satisfies the query condition in the association information tree;
    获取查找到的信息节点对应的制度子文件，将所述制度子文件拆分为多个文件片段，将多个所述文件片段推送至所述第一终端；Obtaining a system sub-file corresponding to the found information node, splitting the system sub-file into a plurality of file segments, and pushing a plurality of the file segments to the first terminal;
    捕获所述第一终端发生的对所述文件片段的学习事件，获取所述学习事件对应的制度学习数据；所述制度学习数据包括有效学习时间；及Capturing a learning event of the file segment that occurs in the first terminal, acquiring system learning data corresponding to the learning event; and the system learning data includes an effective learning time;
    当所述有效学习时间达到阈值时，获取目标资源，将所述目标资源转移至所述第一终端。When the valid learning time reaches the threshold, the target resource is acquired, and the target resource is transferred to the first terminal.
  10. 根据权利要求9所述的计算机设备，其特征在于，所述处理器执行所述计算机可读指令时还执行以下步骤：The computer apparatus according to claim 9, wherein said processor further performs the following steps when said computer readable instructions are executed:
    监测第二终端发布的制度信息；所述制度信息包括制度描述信息及关联的制度文件；所述制度文件包括多个制度条款以及每个制度条款对应的适用对象标识；Monitoring system information issued by the second terminal; the system information includes system description information and associated system documents; the system file includes a plurality of system clauses and an applicable object identifier corresponding to each system clause;
    对所述制度信息进行分类，根据分类结果将所述制度信息添加至预设的一个或多个目标信息树；Classifying the system information, and adding the system information to a preset one or more target information trees according to the classification result;
    获取所述目标信息树对应的多个关联信息树；每个所述关联信息树具有对应的适用对象标识；Acquiring a plurality of association information trees corresponding to the target information tree; each of the association information trees has a corresponding applicable object identifier;
    对所述制度文件进行拆分，利用每个适用对象标识对应的制度条款生成相应适用对象标识对应的制度子文件；及Separating the system files, and using the system terms corresponding to each applicable object identifier to generate a system sub-file corresponding to the applicable object identifier; and
    将每个所述适用对象标识对应的制度描述信息和制度子文件添加至相应的关联信息 树。The system description information and the system sub-file corresponding to each of the applicable object identifiers are added to the corresponding association information tree.
  11. 根据权利要求9所述的计算机设备，其特征在于，所述处理器执行所述计算机可读指令时还执行以下步骤：The computer apparatus according to claim 9, wherein said processor further performs the following steps when said computer readable instructions are executed:
    对所述制度信息进行分词得到对应的原始词语集合；所述原始词语集合包括多个原始词语；Performing word segmentation on the system information to obtain a corresponding original word set; the original word set includes a plurality of original words;
    对各个原始词语进行同义扩展，生成每个原始词语对应的扩展词语集合；Synchronous expansion of each original word to generate a set of extended words corresponding to each original word;
    根据各个扩展词语集合形成所述制度信息对应的扩展制度信息集合；Forming an extended system information set corresponding to the system information according to each set of extended words;
    将所述扩展制度信息集合输入预设的制度管理模型，得到所述制度信息对应的目标类别；及Inputting the extended system information set into a preset system management model to obtain a target category corresponding to the system information; and
    获取多个所述目标信息树分别对应的类别标注，筛选包含与所述目标类别对应类别标注的目标信息树，将所述制度信息添加至筛选得到的目标信息树。Obtaining a category label corresponding to each of the plurality of target information trees, filtering a target information tree including a category label corresponding to the target category, and adding the system information to the filtered target information tree.
  12. 根据权利要求9所述的计算机设备，其特征在于，所述处理器执行所述计算机可读指令时还执行以下步骤：The computer apparatus according to claim 9, wherein said processor further performs the following steps when said computer readable instructions are executed:
    当接收到所述制度学习请求时，随机生成密钥字符串；When the system learning request is received, a key string is randomly generated;
    获取预存储的私钥，利用所述私钥对所述密钥字符串进行非对称加密，将加密后的所述密钥字符串发送至所述第一终端；Obtaining a pre-stored private key, performing asymmetric encryption on the key string by using the private key, and sending the encrypted key string to the first terminal;
    当拆分得到所述文件片段时，定位所述制度子文件中的敏感字段，使用随机生成的密钥字符串对称加密所述敏感字段，生成文件片段对应的制度密文；When the file fragment is obtained by splitting, the sensitive field in the system sub-file is located, and the sensitive field is symmetrically encrypted using a randomly generated key string to generate an institutional ciphertext corresponding to the file fragment;
    将所述制度密文发送至所述第一终端；所述方法还包括：Sending the system ciphertext to the first terminal; the method further includes:
    获取所述第一终端在监控时段对所述制度密文操作的解密失败次数；Acquiring the number of times the first terminal decrypts the system ciphertext operation during the monitoring period;
    根据所述解密失败次数，计算所述业务终端对应的信息泄漏风险值；及Calculating an information leakage risk value corresponding to the service terminal according to the number of decryption failures; and
    当所述信息泄漏风险值超过阈值时，降低所述第一终端的制度查询权限。When the information leakage risk value exceeds a threshold, the system query authority of the first terminal is lowered.
  13. 根据权利要求9所述的计算机设备，其特征在于，所述处理器执行所述计算机可读指令时还执行以下步骤：The computer apparatus according to claim 9, wherein said processor further performs the following steps when said computer readable instructions are executed:
    获取所述制度子文件的文件类型；Obtaining the file type of the system sub-file;
    根据所述文件类型，获取对应的数据量阈值；Obtaining a corresponding data amount threshold according to the file type;
    根据所述数据量阈值对所述制度子文件进行拆分，得到多个文件片段；及Splitting the system sub-file according to the data amount threshold to obtain a plurality of file segments; and
    根据拆分顺序，将多个所述文件片段依次推送至所述第一终端。A plurality of the file segments are sequentially pushed to the first terminal according to a splitting order.
  14. 根据权利要求9所述的计算机设备，其特征在于，所述文件片段包括文档片段；所述学习事件包括文档关闭事件；所述处理器执行所述计算机可读指令时还执行以下步骤：The computer apparatus according to claim 9, wherein said file fragment comprises a document fragment; said learning event comprises a document close event; and said processor, when said computer readable instructions are executed, further performing the following steps:
    捕获所述第一终端发生的对所述文档片段的实际阅读时间；Capturing an actual reading time of the document segment that occurs by the first terminal;
    获取所述文档片段的数据量，根据所述数据量计算所述文档片段对应的常规阅读时间；Obtaining an amount of data of the document segment, and calculating a regular reading time corresponding to the document segment according to the data amount;
    当捕获到所述文档关闭事件时，记录所述文档片段的阅读位置，根据所述文档片段生 成随机测评问卷，将所述随机测评问卷发送至所述第一终端；Recording a reading position of the document segment when the document closing event is captured, generating a random evaluation questionnaire according to the document segment, and transmitting the random evaluation questionnaire to the first terminal;
    接收所述第一终端在预设时长内返回的所述随机测评问卷的答案信息，对所述答案信息进行打分，得到测评分值；及Receiving the answer information of the random evaluation questionnaire returned by the first terminal within a preset duration, and scoring the answer information to obtain a score value; and
    根据所述测评分值、所述实际阅读时间以及所述常规阅读时间，计算所述第一终端对应的有效学习时间。Calculating an effective learning time corresponding to the first terminal according to the measured score value, the actual reading time, and the regular reading time.
  15. 一个或多个存储有计算机可读指令的非易失性计算机可读存储介质，所述计算机可读指令被一个或多个处理器执行时，使得所述一个或多个处理器执行以下步骤：One or more non-transitory computer readable storage mediums storing computer readable instructions, when executed by one or more processors, cause the one or more processors to perform the following steps:
    接收第一终端发送的制度学习请求，所述制度学习请求携带了适用对象标识和查询条件；Receiving an institutional learning request sent by the first terminal, where the system learning request carries an applicable object identifier and a query condition;
    获取所述适用对象标识对应的关联信息树；所述关联信息树包括多个信息节点及每个所述信息节点关联的多个制度子文件；Obtaining an association information tree corresponding to the applicable object identifier; the association information tree includes a plurality of information nodes and a plurality of system sub-files associated with each of the information nodes;
    在所述关联信息树中查找满足所述查询条件的信息节点；Finding an information node that satisfies the query condition in the association information tree;
    获取查找到的信息节点对应的制度子文件，将所述制度子文件拆分为多个文件片段，将多个所述文件片段推送至所述第一终端；Obtaining a system sub-file corresponding to the found information node, splitting the system sub-file into a plurality of file segments, and pushing a plurality of the file segments to the first terminal;
    捕获所述第一终端发生的对所述文件片段的学习事件，获取所述学习事件对应的制度学习数据；所述制度学习数据包括有效学习时间；及Capturing a learning event of the file segment that occurs in the first terminal, acquiring system learning data corresponding to the learning event; and the system learning data includes an effective learning time;
    当所述有效学习时间达到阈值时，获取目标资源，将所述目标资源转移至所述第一终端。When the valid learning time reaches the threshold, the target resource is acquired, and the target resource is transferred to the first terminal.
  16. 根据权利要求15所述的存储介质，其特征在于，所述计算机可读指令被所述处理器执行时还执行以下步骤：The storage medium of claim 15 wherein said computer readable instructions, when executed by said processor, further perform the following steps:
    监测第二终端发布的制度信息；所述制度信息包括制度描述信息及关联的制度文件；所述制度文件包括多个制度条款以及每个制度条款对应的适用对象标识；Monitoring system information issued by the second terminal; the system information includes system description information and associated system documents; the system file includes a plurality of system clauses and an applicable object identifier corresponding to each system clause;
    对所述制度信息进行分类，根据分类结果将所述制度信息添加至预设的一个或多个目标信息树；Classifying the system information, and adding the system information to a preset one or more target information trees according to the classification result;
    获取所述目标信息树对应的多个关联信息树；每个所述关联信息树具有对应的适用对象标识；Acquiring a plurality of association information trees corresponding to the target information tree; each of the association information trees has a corresponding applicable object identifier;
    对所述制度文件进行拆分，利用每个适用对象标识对应的制度条款生成相应适用对象标识对应的制度子文件；及Separating the system files, and using the system terms corresponding to each applicable object identifier to generate a system sub-file corresponding to the applicable object identifier; and
    将每个所述适用对象标识对应的制度描述信息和制度子文件添加至相应的关联信息树。The system description information and the system sub-file corresponding to each of the applicable object identifiers are added to the corresponding association information tree.
  17. 根据权利要求15所述的存储介质，其特征在于，所述计算机可读指令被所述处理器执行时还执行以下步骤：The storage medium of claim 15 wherein said computer readable instructions, when executed by said processor, further perform the following steps:
    对所述制度信息进行分词得到对应的原始词语集合；所述原始词语集合包括多个原始词语；Performing word segmentation on the system information to obtain a corresponding original word set; the original word set includes a plurality of original words;
    对各个原始词语进行同义扩展，生成每个原始词语对应的扩展词语集合；Synchronous expansion of each original word to generate a set of extended words corresponding to each original word;
    根据各个扩展词语集合形成所述制度信息对应的扩展制度信息集合；Forming an extended system information set corresponding to the system information according to each set of extended words;
    将所述扩展制度信息集合输入预设的制度管理模型，得到所述制度信息对应的目标类别；及Inputting the extended system information set into a preset system management model to obtain a target category corresponding to the system information; and
    获取多个所述目标信息树分别对应的类别标注，筛选包含与所述目标类别对应类别标注的目标信息树，将所述制度信息添加至筛选得到的目标信息树。Obtaining a category label corresponding to each of the plurality of target information trees, filtering a target information tree including a category label corresponding to the target category, and adding the system information to the filtered target information tree.
  18. 根据权利要求15所述的存储介质，其特征在于，所述计算机可读指令被所述处理器执行时还执行以下步骤：The storage medium of claim 15 wherein said computer readable instructions, when executed by said processor, further perform the following steps:
    当接收到所述制度学习请求时，随机生成密钥字符串；When the system learning request is received, a key string is randomly generated;
    获取预存储的私钥，利用所述私钥对所述密钥字符串进行非对称加密，将加密后的所述密钥字符串发送至所述第一终端；Obtaining a pre-stored private key, performing asymmetric encryption on the key string by using the private key, and sending the encrypted key string to the first terminal;
    当拆分得到所述文件片段时，定位所述制度子文件中的敏感字段，使用随机生成的密钥字符串对称加密所述敏感字段，生成文件片段对应的制度密文；When the file fragment is obtained by splitting, the sensitive field in the system sub-file is located, and the sensitive field is symmetrically encrypted using a randomly generated key string to generate an institutional ciphertext corresponding to the file fragment;
    将所述制度密文发送至所述第一终端；所述方法还包括：Sending the system ciphertext to the first terminal; the method further includes:
    获取所述第一终端在监控时段对所述制度密文操作的解密失败次数；Acquiring the number of times the first terminal decrypts the system ciphertext operation during the monitoring period;
    根据所述解密失败次数，计算所述业务终端对应的信息泄漏风险值；及Calculating an information leakage risk value corresponding to the service terminal according to the number of decryption failures; and
    当所述信息泄漏风险值超过阈值时，降低所述第一终端的制度查询权限。When the information leakage risk value exceeds a threshold, the system query authority of the first terminal is lowered.
  19. 根据权利要求15所述的存储介质，其特征在于，所述计算机可读指令被所述处理器执行时还执行以下步骤：The storage medium of claim 15 wherein said computer readable instructions, when executed by said processor, further perform the following steps:
    获取所述制度子文件的文件类型；Obtaining the file type of the system sub-file;
    根据所述文件类型，获取对应的数据量阈值；Obtaining a corresponding data amount threshold according to the file type;
    根据所述数据量阈值对所述制度子文件进行拆分，得到多个文件片段；及Splitting the system sub-file according to the data amount threshold to obtain a plurality of file segments; and
    根据拆分顺序，将多个所述文件片段依次推送至所述第一终端。A plurality of the file segments are sequentially pushed to the first terminal according to a splitting order.
  20. 根据权利要求15所述的存储介质，其特征在于，所述文件片段包括文档片段；所述学习事件包括文档关闭事件；所述计算机可读指令被所述处理器执行时还执行以下步骤：The storage medium of claim 15 wherein said file fragment comprises a document fragment; said learning event comprises a document close event; said computer readable instructions being executed by said processor further performing the following steps:
    捕获所述第一终端发生的对所述文档片段的实际阅读时间；Capturing an actual reading time of the document segment that occurs by the first terminal;
    获取所述文档片段的数据量，根据所述数据量计算所述文档片段对应的常规阅读时间；Obtaining an amount of data of the document segment, and calculating a regular reading time corresponding to the document segment according to the data amount;
    当捕获到所述文档关闭事件时，记录所述文档片段的阅读位置，根据所述文档片段生成随机测评问卷，将所述随机测评问卷发送至所述第一终端；Recording a reading position of the document segment when the document closing event is captured, generating a random evaluation questionnaire according to the document segment, and transmitting the random evaluation questionnaire to the first terminal;
    接收所述第一终端在预设时长内返回的所述随机测评问卷的答案信息，对所述答案信息进行打分，得到测评分值；及Receiving the answer information of the random evaluation questionnaire returned by the first terminal within a preset duration, and scoring the answer information to obtain a score value; and
    根据所述测评分值、所述实际阅读时间以及所述常规阅读时间，计算所述第一终端对应的有效学习时间。Calculating an effective learning time corresponding to the first terminal according to the measured score value, the actual reading time, and the regular reading time.
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Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111274782A (en) * 2020-02-25 2020-06-12 平安科技（深圳）有限公司 Text auditing method and device, computer equipment and readable storage medium
CN111400170A (en) * 2020-02-29 2020-07-10 中国平安人寿保险股份有限公司 Data permission testing method and device
CN112148606A (en) * 2020-09-22 2020-12-29 京东数字科技控股股份有限公司 Embedded point testing method, device, equipment and computer readable medium
CN112711648A (en) * 2020-12-23 2021-04-27 航天信息股份有限公司 Database character string ciphertext storage method, electronic device and medium
CN112733188A (en) * 2021-01-13 2021-04-30 航天晨光股份有限公司 Sensitive file management method
CN113407494A (en) * 2021-05-27 2021-09-17 东软集团股份有限公司 Illegal file detection method, device and equipment
CN114401289A (en) * 2021-12-31 2022-04-26 深圳市麦谷科技有限公司 Task batch uploading method and system
CN114661238A (en) * 2022-03-29 2022-06-24 江苏安超云软件有限公司 Method for recovering storage system space with cache and application
CN116720172A (en) * 2023-08-07 2023-09-08 四川神州行网约车服务有限公司 Verification method and device for system permission, computer equipment and readable storage medium

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110222286A (en) * 2019-05-21 2019-09-10 平安普惠企业管理有限公司 Information acquisition method, device, terminal and computer readable storage medium
CN111428967A (en) * 2020-03-02 2020-07-17 四川宝石花鑫盛油气运营服务有限公司 File management method and device based on post as basic unit
CN111880778B (en) * 2020-06-30 2023-12-22 百度在线网络技术（北京）有限公司 Method and device for generating interface document, electronic equipment and storage medium
CN116527982B (en) * 2023-06-01 2023-09-15 杭州威灿科技有限公司 Method and system for recording question synchronous audio and video

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105913172A (en) * 2016-04-05 2016-08-31 浪潮电子信息产业股份有限公司 Business platform and employee evaluation method
CN106886962A (en) * 2017-02-27 2017-06-23 湖南润安危物联科技发展有限公司 training process management method, device and system
US20170220974A1 (en) * 2016-01-29 2017-08-03 Sap Se Resource optimization for production efficiency

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6253195B1 (en) * 1998-09-21 2001-06-26 Microsoft Corporation Optimized query tree
US8489644B2 (en) * 2006-04-05 2013-07-16 Ca, Inc. System and method for managing virtual tree pages
CN103500216B (en) * 2013-09-30 2017-02-15 北京林业大学 Method for extracting file information
CN106970928B (en) * 2016-01-14 2020-12-29 平安科技（深圳）有限公司 File management method and system
CN107562835B (en) * 2017-08-23 2020-03-27 Oppo广东移动通信有限公司 File searching method and device, mobile terminal and computer readable storage medium
CN107784067B (en) * 2017-08-31 2020-05-26 平安科技（深圳）有限公司 Monitoring information processing method, device, server and storage medium

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20170220974A1 (en) * 2016-01-29 2017-08-03 Sap Se Resource optimization for production efficiency
CN105913172A (en) * 2016-04-05 2016-08-31 浪潮电子信息产业股份有限公司 Business platform and employee evaluation method
CN106886962A (en) * 2017-02-27 2017-06-23 湖南润安危物联科技发展有限公司 training process management method, device and system

Cited By (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111274782A (en) * 2020-02-25 2020-06-12 平安科技（深圳）有限公司 Text auditing method and device, computer equipment and readable storage medium
CN111274782B (en) * 2020-02-25 2023-10-20 平安科技（深圳）有限公司 Text auditing method and device, computer equipment and readable storage medium
CN111400170A (en) * 2020-02-29 2020-07-10 中国平安人寿保险股份有限公司 Data permission testing method and device
CN111400170B (en) * 2020-02-29 2024-06-07 中国平安人寿保险股份有限公司 Data authority testing method and device
CN112148606A (en) * 2020-09-22 2020-12-29 京东数字科技控股股份有限公司 Embedded point testing method, device, equipment and computer readable medium
CN112148606B (en) * 2020-09-22 2024-05-17 京东科技控股股份有限公司 Buried point test method, buried point test device, buried point test equipment and computer readable medium
CN112711648A (en) * 2020-12-23 2021-04-27 航天信息股份有限公司 Database character string ciphertext storage method, electronic device and medium
CN112733188B (en) * 2021-01-13 2023-09-22 航天晨光股份有限公司 Sensitive file management method
CN112733188A (en) * 2021-01-13 2021-04-30 航天晨光股份有限公司 Sensitive file management method
CN113407494A (en) * 2021-05-27 2021-09-17 东软集团股份有限公司 Illegal file detection method, device and equipment
CN113407494B (en) * 2021-05-27 2024-02-09 东软集团股份有限公司 Illegal file detection method, device and equipment
CN114401289A (en) * 2021-12-31 2022-04-26 深圳市麦谷科技有限公司 Task batch uploading method and system
CN114661238A (en) * 2022-03-29 2022-06-24 江苏安超云软件有限公司 Method for recovering storage system space with cache and application
CN114661238B (en) * 2022-03-29 2024-01-02 江苏安超云软件有限公司 Method for recovering storage system space with cache and application
CN116720172A (en) * 2023-08-07 2023-09-08 四川神州行网约车服务有限公司 Verification method and device for system permission, computer equipment and readable storage medium
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