CN111667141A - Pending task case processing method, device, equipment and storage medium - Google Patents
Pending task case processing method, device, equipment and storage medium Download PDFInfo
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Abstract
The invention relates to the field of cloud services, and discloses a pending task case processing method, device, equipment and storage medium, which are used for improving the processing efficiency of flow breakpoints of pending task cases. The processing method of the pending task case comprises the following steps: acquiring pending task cases to be processed, performing data analysis on the pending task cases according to a preset abnormal state analysis strategy to identify original abnormal cases in the pending task cases, and storing the original abnormal cases in a preset monitoring pool; performing data analysis on the original abnormal cases in the preset monitoring pool according to the abnormal state analysis strategy to identify target abnormal cases in the preset monitoring pool; acquiring rule information and case information of a target abnormal case; comparing and analyzing the case information and the rule information, and determining a target information element required for terminating the abnormal case; and sending the target information element to the user terminal. In addition, the invention also relates to a block chain technology, and the target information element can be stored in the block chain node.
Description
Technical Field
The present invention relates to the field of status monitoring, and in particular, to a method, an apparatus, a device, and a storage medium for processing a pending task case.
Background
In the business case processing flow, a client and a business case handler need to communicate for many times and interact with different data and materials, and the development of many flow links depends on the last flow link. Due to the complexity and dependency of the process interaction, the progress and processing quality of the service case are seriously affected by the breakpoints in the multiple processes of the same service case, and therefore, the process breakpoints in the service case need to be monitored.
In the prior art, business case statistics is periodically carried out manually or non-real-time data monitoring is carried out through big data calculation, so that the problem that the business case flow breakpoints cannot be effectively and timely fed back to clients or business case handlers so as to effectively process the flow breakpoints of the business cases exists, and the processing efficiency of the flow breakpoints of the pending task cases is low.
Disclosure of Invention
The invention mainly aims to solve the problem of low processing efficiency of flow breakpoints of pending task cases.
The invention provides a pending task case processing method in a first aspect, which comprises the following steps:
acquiring pending task cases to be processed, wherein the pending task cases are cases which are located in target process nodes but not terminate the processes;
performing data analysis on the pending task cases according to a preset abnormal state analysis strategy to identify original abnormal cases in the pending task cases, and storing the original abnormal cases into a preset monitoring pool, wherein the abnormal state analysis strategy is used for analyzing whether information of process nodes and unprocessed retention time meet preset conditions, and the preset monitoring pool is a plurality of monitoring pools in different preset time periods;
analyzing data of the original abnormal cases in the preset monitoring pool according to the abnormal state analysis strategy so as to identify target abnormal cases in the preset monitoring pool;
acquiring rule information and case information of the target abnormal case, wherein the rule information is a condition required for terminating the target abnormal case, and the case information is an information element included in the target abnormal case;
comparing and analyzing the case information and the rule information, and determining a target information element required for terminating the target abnormal case;
and sending the target information element to a user terminal.
Optionally, in a first implementation manner of the first aspect of the present invention, the performing data analysis on the original abnormal case in the preset monitoring pool according to the abnormal state analysis policy to identify the target abnormal case in the preset monitoring pool includes:
performing data analysis on the original abnormal cases stored in the monitoring pool in the first preset time period according to the abnormal state analysis strategy to obtain candidate abnormal cases;
storing the candidate abnormal cases in a monitoring pool of a second preset time period, wherein the starting time of the second preset time period is later than the ending time of the first preset time period;
and performing iteration data analysis on the candidate abnormal cases in the monitoring pool in the second preset time period according to the abnormal state analysis strategy to obtain target abnormal cases.
Optionally, in a second implementation manner of the first aspect of the present invention, the performing data analysis on the original abnormal case stored in the monitoring pool in the first preset time period according to the abnormal state analysis policy to obtain a candidate abnormal case includes:
acquiring a target moment, and judging whether the target moment is the end moment of the first preset time period or not;
and if the target time is the end time of the first preset time period, performing data analysis on the original abnormal case stored in the monitoring pool of the first preset time period according to the abnormal state analysis strategy to obtain a candidate abnormal case.
Optionally, in a third implementation manner of the first aspect of the present invention, the comparing and analyzing the case information and the rule information, and determining a target information element required for terminating the target abnormal case includes:
creating a case knowledge graph of the case information and a rule knowledge graph of the rule information, and carrying out random walk on the case knowledge graph and the rule knowledge graph to obtain a corresponding case information sequence and a corresponding rule information sequence;
calculating cosine similarity between the case information sequence and the rule information sequence to obtain a similarity value;
and determining an information element in the case information with the similarity value larger than a preset threshold value as a target information element, wherein the target information element is stored in a block chain.
Optionally, in a fourth implementation manner of the first aspect of the present invention, the obtaining rule information and case information of the target abnormal case includes:
acquiring the case number and the rule number of the target abnormal case according to the case state of the target abnormal case;
sending the case number and the rule number to a preset rule engine, and traversing a preset rule tree through the rule engine to obtain rule information corresponding to the rule number;
and generating a key value of the case number through the rule engine and retrieving a preset case hash table to obtain case information corresponding to the key value.
Optionally, in a fifth implementation manner of the first aspect of the present invention, the sending the target information element to the user terminal includes:
generating a visual chart of the target information element according to a preset feedback processing strategy, and rendering the visual chart to a preset display page;
judging whether a case processing request based on the visual chart returned by the preset display page is received in a third preset time period;
and when a case processing request based on the visual chart returned by the preset display page is not received in a third preset time period, sending the target information element to a user terminal.
Optionally, in a sixth implementation manner of the first aspect of the present invention, before the acquiring the pending task case to be processed, the method further includes:
acquiring pre-stored case information, case numbers and case states of business cases which are located at target process nodes but not terminate the processes, and setting rule information and feedback processing strategies of the business cases and rule numbers of the rule information through a preset rule engine;
and creating a corresponding relation among the case information, the case number, the case state, the rule information, the processing strategy and the rule number, and determining the business case with the corresponding relation as a pending task case to be processed.
A second aspect of the present invention provides a pending task case processing apparatus, comprising:
the system comprises a first acquisition module, a second acquisition module and a processing module, wherein the first acquisition module is used for acquiring pending task cases to be processed, and the pending task cases are cases which are located in a target process node but not terminate a process;
the system comprises a first data analysis module, a second data analysis module and a third data analysis module, wherein the first data analysis module is used for carrying out data analysis on the pending task cases according to a preset abnormal state analysis strategy so as to identify original abnormal cases in the pending task cases and store the original abnormal cases into a preset monitoring pool, the abnormal state analysis strategy is used for analyzing whether information of process nodes and unprocessed retention time meet preset conditions, and the preset monitoring pool is a plurality of monitoring pools in different preset time periods;
the second data analysis module is used for carrying out data analysis on the original abnormal cases in the preset monitoring pool according to the abnormal state analysis strategy so as to identify target abnormal cases in the preset monitoring pool;
a second obtaining module, configured to obtain rule information and case information of the target abnormal case, where the rule information is a condition required to terminate the target abnormal case, and the target case information is an information element included in the abnormal case;
the comparison analysis module is used for comparing and analyzing the case information and the rule information and determining a target information element required for terminating the target abnormal case;
and the sending module is used for sending the target information element to the user terminal.
Optionally, in a first implementation manner of the second aspect of the present invention, the second data analysis module includes:
the first data analysis unit is used for carrying out data analysis on the original abnormal cases stored in the monitoring pool in a first preset time period according to the abnormal state analysis strategy to obtain candidate abnormal cases;
the storage unit is used for storing the candidate abnormal cases in a monitoring pool of a second preset time period, wherein the starting time of the second preset time period is later than the ending time of the first preset time period;
and the second data analysis unit is used for carrying out iterative data analysis on the candidate abnormal cases in the monitoring pool in the second preset time interval according to the abnormal state analysis strategy to obtain target abnormal cases.
Optionally, in a second implementation manner of the second aspect of the present invention, the first data analysis unit is specifically configured to:
acquiring a target moment, and judging whether the target moment is the end moment of the first preset time period or not;
and if the target time is the end time of the first preset time period, performing data analysis on the original abnormal case stored in the monitoring pool of the first preset time period according to the abnormal state analysis strategy to obtain a candidate abnormal case.
Optionally, in a third implementation manner of the second aspect of the present invention, the comparative analysis module is specifically configured to:
creating a case knowledge graph of the case information and a rule knowledge graph of the rule information, and carrying out random walk on the case knowledge graph and the rule knowledge graph to obtain a corresponding case information sequence and a corresponding rule information sequence;
calculating cosine similarity between the case information sequence and the rule information sequence to obtain a similarity value;
and determining an information element in the case information with the similarity value larger than a preset threshold value as a target information element, wherein the target information element is stored in a block chain.
Optionally, in a fourth implementation manner of the second aspect of the present invention, the second obtaining module is specifically configured to:
acquiring the case number and the rule number of the target abnormal case according to the case state of the target abnormal case;
sending the case number and the rule number to a preset rule engine, and traversing a preset rule tree through the rule engine to obtain rule information corresponding to the rule number;
and generating a key value of the case number through the rule engine and retrieving a preset case hash table to obtain case information corresponding to the key value.
Optionally, in a fifth implementation manner of the second aspect of the present invention, the sending module includes:
the generating unit is used for generating a visual chart of the target information element according to a preset feedback processing strategy and rendering the visual chart to a preset display page;
the judging unit is used for judging whether a case processing request based on the visual chart returned by the preset display page is received in a third preset time period;
and the sending unit is used for sending the target information element to a user terminal when a case processing request based on the visual chart returned by the preset display page is not received in a third preset time period.
Optionally, in a sixth implementation manner of the second aspect of the present invention, the processing device of a pending task case includes:
the system comprises a setting module, a feedback processing module and a processing module, wherein the setting module is used for acquiring pre-stored case information, case numbers and case states of business cases which are located at target process nodes but not terminate processes, and setting rule information and feedback processing strategies of the business cases and rule numbers of the rule information through a preset rule engine;
and the creating module is used for creating the corresponding relation among the case information, the case number, the case state, the rule information, the processing strategy and the rule number, and determining the business case with the corresponding relation as a pending task case to be processed.
A third aspect of the present invention provides a pending task case processing apparatus, comprising: a memory having instructions stored therein and at least one processor, the memory and the at least one processor interconnected by a line; the at least one processor invokes the instructions in the memory to cause the processing device of the pending task case to perform the above-described processing method of the pending task case.
A fourth aspect of the present invention provides a computer-readable storage medium having stored therein instructions, which, when run on a computer, cause the computer to perform the above-mentioned method of handling a pending task case.
In the technical scheme provided by the invention, pending task cases to be processed are obtained; performing data analysis on the pending task cases according to a preset abnormal state analysis strategy to identify original abnormal cases in the pending task cases, and storing the original abnormal cases into a preset monitoring pool; performing data analysis on the original abnormal cases in the preset monitoring pool according to the abnormal state analysis strategy to identify target abnormal cases in the preset monitoring pool; acquiring rule information and case information of a target abnormal case; comparing and analyzing the case information and the rule information, and determining a target information element required for terminating the abnormal case; and sending the target information element to the user terminal. In the invention, the pending task case is monitored and judged in real time through the preset abnormal state analysis strategy, the change of the service can be flexibly responded, the flow breakpoint data of the pending task case is monitored in quasi-real time, the monitoring result is fed back in time, and the processing efficiency of the flow breakpoint of the pending task case is improved.
Drawings
FIG. 1 is a diagram of a pending task case processing method according to an embodiment of the present invention;
FIG. 2 is a diagram of another embodiment of a method for handling a pending task case according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an embodiment of a processing device for pending task cases in an embodiment of the present invention;
FIG. 4 is a schematic diagram of another embodiment of a processing device for pending task cases according to an embodiment of the present invention;
FIG. 5 is a diagram of an embodiment of a processing device for a pending task case in an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a method, a device, equipment and a storage medium for processing a pending task case, which can carry out real-time monitoring and state judgment on the pending task case through an abnormal state analysis strategy, flexibly respond to the change of a service, monitor the flow breakpoint data of the pending task case in a quasi-real-time manner and feed back the monitoring result in time, and improve the processing efficiency of the flow breakpoint of the pending task case.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," or "having," and any variations thereof, are intended to cover non-exclusive inclusions, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
For ease of understanding, a detailed flow of an embodiment of the present invention is described below, and referring to fig. 1, an embodiment of a method for processing a pending task case in an embodiment of the present invention includes:
101. acquiring pending task cases to be processed, wherein the pending task cases are cases which are located in target process nodes but not terminate the processes;
it is understood that the executing body of the present invention may be a processing device of a pending task case, and may also be a terminal or a server, which is not limited herein. The embodiment of the present invention is described by taking a server as an execution subject.
The server may detect the state of the flow node of the case, and when it is detected that the state of the flow node is that the current flow node is not terminated to enter the next flow node, the corresponding case is taken as a pending task case, for example: in the claim case, documents need to be uploaded to settle, but the fact that the client or the surveyor does not upload the documents leads the claim case not to enter the next flow node, the claim case is a pending task case.
102. Performing data analysis on the pending task cases according to a preset abnormal state analysis strategy to identify original abnormal cases in the pending task cases, and storing the original abnormal cases into a preset monitoring pool, wherein the abnormal state analysis strategy is used for analyzing whether the information of the process nodes and the unprocessed retention time meet preset conditions, and the preset monitoring pool is a plurality of monitoring pools in different preset time periods;
the server analyzes whether the information or the data required to be submitted in the information of the current process node is complete and correct or not according to the preset abnormal state analysis strategy, analyzes whether the unprocessed retention time of the current process node exceeds the preset time or not so as to analyze the abnormal state, and takes the pending task case with the incomplete and/or correct information or the data required to be submitted in the information of the current process node and the unprocessed retention time of the current process node exceeding the preset time as the original abnormal case.
After the server obtains the original abnormal case, the original abnormal case is stored in a preset monitoring pool with a certain time length and different preset time periods in a key value mode through a preset data structure server Redis cache mechanism, for example: the preset monitoring pool is set to have the time length of 1 hour, two different preset time periods are 14:00-15:00 and 15:00-16:00, the original abnormal case is stored in the preset monitoring pool in the preset time period of 14:00-15:00, the original abnormal case in the preset monitoring pool in the preset time period of 14:00-15:00 is subjected to data analysis (abnormal state analysis can be performed) to obtain a case to be processed, and the case to be processed is stored in the preset monitoring pool in the preset time period of 15:00-16: 00.
103. Performing data analysis on the original abnormal cases in the preset monitoring pool according to the abnormal state analysis strategy to identify target abnormal cases in the preset monitoring pool;
the server analyzes the abnormal state of the current process node state of the original abnormal case in the preset monitoring pool at different preset time intervals according to the abnormal state analysis strategy, analyzes whether the information or the data required to be submitted in the information of the current process node of the original abnormal case is complete and correct, analyzes whether the unprocessed retention time of the current process node of the original abnormal case exceeds the preset time, analyzes the abnormal state, and takes the pending task case as the target abnormal case, wherein the information or the data required to be submitted in the information of the current process node of the original abnormal case is incomplete and/or correct, and the unprocessed retention time of the current process node of the original abnormal case exceeds the preset time.
Optionally, the server may scan a preset database in the preset monitoring pool through a preset timing task mechanism to obtain a newly added case in the preset monitoring pool, and perform secondary abnormal state analysis processing on the newly added case and an original abnormal case before the newly added case is stored in the preset monitoring pool, so as to obtain a target abnormal case, where the newly added case is, for example: the time period for presetting the monitoring pool corresponds to 12: 00-13:00, scanning and detecting a preset database corresponding to the preset monitoring pool through a preset timing task mechanism to obtain 12: and newly storing original abnormal cases within the time period of 00-13: 00.
104. Acquiring rule information and case information of a target abnormal case, wherein the rule information is a condition required for terminating the target abnormal case, and the case information is an information element included by the target abnormal case;
the server can extract the case number and the rule number from the tag information of the target abnormal case through a note extraction algorithm, wherein the case number and the rule number in the tag information are configured in advance. And sending the case number and the rule number to a preset rule engine in a parameter form, retrieving by the rule engine according to the case number to obtain corresponding case information, and retrieving according to the rule number to obtain corresponding rule information.
The rule information is a condition required for terminating the flow node of the target abnormal case, for example: the flow nodes of the target abnormal cases need to submit complete and correct claim settlement documents, the submitted users need to submit both the A party and the B party, and images of the submitted claim settlement documents are clear. The case information may be information of a current process node in the target abnormal case, and may also be termination conditions that need to be satisfied correspondingly by the information of the current process node in the target abnormal case and the information of the current process node, for example: the case information of the target abnormal case is the specific information of the claim settlement document submitted in the current process node of the target abnormal case; or, the case information of the target abnormal case is the specific information of the claim settlement document submitted in the current process node of the target abnormal case and the condition information (information element) that the information of the claim settlement document needs to satisfy to terminate the current process node.
105. Comparing and analyzing the case information and the rule information, and determining a target information element required for terminating the target abnormal case;
the server analyzes whether the case corresponding to the case information is a case requiring further processing through comparison of the rule information to determine target information elements, such as: the case information is that X submits an A financial document of an X company and a B financial document of an X user when X is X X days X in X months X years for a current process node, the information in the A financial document is C (specifically comprising C1, C2 and C3), the information in the B financial document is D (specifically comprising D1, D2 and D3), C1, C2 and C3 are respectively identical to E1, E2 and E3 (same information elements) through comparison analysis of C and D with rule information (conditions E1, E2, E3, E4 and E5 required for terminating the current process node), D1, D2 and D2 are respectively identical to E2, E2 and E2 (same information elements), E2 and E2 are respectively identical to target information elements 1 corresponding to the A financial document, E2 and E72 are respectively identical to target information elements 1, and E362 is target information elements corresponding to the case information elements, wherein target elements are target elements of abnormal target documents 1 and target documents 2, when performing the comparative analysis, information elements with vector similarity greater than the first threshold may be regarded as the same information element by calculating the vector similarity between the case information and the rule information.
106. And sending the target information element to the user terminal.
The server retrieves a corresponding processing policy by matching the processing policy corresponding to the rule information, or by using the root rule information, where the processing policy includes a transmission route of the target information element, for example: short message, telephone, WeChat, email, E-hand and other notification modes. After the server obtains the processing policy, the server generates a report or text message or mail format content or visual chart from the target information element according to the notification mode (processing policy), for example: and if the processing strategy is a notification mode of the mail, generating text information from the target information element, and typesetting the text information according to the mail format. And sending the target information element (report or text information or mail format content or visual chart) to the user terminal according to the sending mode corresponding to the notification mode, wherein the user terminal can be a mobile terminal or a server.
It is emphasized that, to further ensure the privacy and security of the target information element, the target information element may also be stored in a node of a block chain.
In the embodiment of the invention, the pending task case is monitored and judged in real time through the abnormal state analysis strategy, the change of the service can be flexibly responded, the flow breakpoint data of the pending task case is monitored in quasi-real time, the monitoring result is fed back in time, and the processing efficiency of the flow breakpoint of the pending task case is improved.
Referring to fig. 2, another embodiment of the method for processing a pending task case according to the embodiment of the present invention includes:
201. acquiring pending task cases to be processed, wherein the pending task cases are cases which are located in target process nodes but not terminate the processes;
it is understood that the executing body of the present invention may be a processing device of a pending task case, and may also be a terminal or a server, which is not limited herein. The embodiment of the present invention is described by taking a server as an execution subject.
Specifically, before the server acquires the pending task case to be processed, the method may further include: acquiring pre-stored case information, case numbers and case states of business cases which are located at target process nodes but not terminate the processes, and setting rule information and feedback processing strategies of the business cases and rule numbers of the rule information through a preset rule engine; and creating a corresponding relation among case information, case numbers, case states, rule information, processing strategies and rule numbers, and determining the business cases with the corresponding relation as pending task cases to be processed.
The server creates a corresponding relation of case information, case numbers, case states, rule information, feedback processing strategies and rule numbers of the business cases which are stored in advance and located at the target process nodes but not terminated, so as to bind the case information, the case numbers, the case states, the feedback processing strategies of the business cases and the rule information and the rule numbers of the preset rule engines. The rule number and the rule information have a corresponding relation, and the corresponding rule information can be obtained according to the rule number; the case number and the case information of the business case have a corresponding relation, and the case information of the corresponding business case can be obtained according to the case number. By establishing the corresponding relation, the corresponding content can be conveniently and effectively retrieved and acquired. The feedback processing strategy is a feedback mode for feeding the target information element back to the user terminal.
202. Performing data analysis on the pending task cases according to a preset abnormal state analysis strategy to identify original abnormal cases in the pending task cases, and storing the original abnormal cases into a preset monitoring pool, wherein the abnormal state analysis strategy is used for analyzing whether the information of the process nodes and the unprocessed retention time meet preset conditions, and the preset monitoring pool is a plurality of monitoring pools in different preset time periods;
the server analyzes whether the information or the data required to be submitted in the information of the current process node is complete and correct or not according to the preset abnormal state analysis strategy, analyzes whether the unprocessed retention time of the current process node exceeds the preset time or not so as to analyze the abnormal state, and takes the pending task case with the incomplete and/or correct information or the data required to be submitted in the information of the current process node and the unprocessed retention time of the current process node exceeding the preset time as the original abnormal case.
After the server obtains the original abnormal case, the original abnormal case is stored in a preset monitoring pool with a certain time length and different preset time periods in a key value mode through a preset data structure server Redis cache mechanism, for example: the preset monitoring pool is set to have the time length of 1 hour correspondingly, two different preset time periods are 14:00-15:00 and 15:00-16:00, the original abnormal case is stored in the preset monitoring pool within the preset time period of 14:00-15:00, the original abnormal case in the preset monitoring pool within the preset time period of 14:00-15:00 is subjected to data analysis (abnormal state analysis can be performed) to obtain a case to be processed, and the case to be processed is stored in the preset monitoring pool within the preset time period of 15:00-16:00
203. Performing data analysis on the original abnormal cases in the preset monitoring pool according to the abnormal state analysis strategy to identify target abnormal cases in the preset monitoring pool;
specifically, the server performs data analysis on the original abnormal cases stored in the monitoring pool in a first preset time period according to an abnormal state analysis strategy to obtain candidate abnormal cases; storing the candidate abnormal cases in a monitoring pool of a second preset time period, wherein the starting time of the second preset time period is later than the ending time of the first preset time period; and performing iteration data analysis on the candidate abnormal cases in the monitoring pool in the second preset time period according to the abnormal state analysis strategy to obtain the target abnormal case.
For example: performing abnormal state analysis on an original abnormal case in a monitoring pool with a first preset time period of 10:00-11:00 according to an abnormal state analysis strategy to obtain a candidate abnormal case (the original abnormal case still in an abnormal state), storing the candidate abnormal case into a monitoring pool with a second preset time period of 11:00-12:00, performing abnormal state analysis on the candidate abnormal case in the monitoring pool with the second preset time period of 11:00-12:00 according to the abnormal state analysis strategy to obtain an abnormal case to be analyzed (the candidate abnormal case still in an abnormal state), repeating the steps until the third preset time period of 20:00-21:00, and taking the abnormal case still in the abnormal state in the monitoring pool of 20:00-21:00 as a target abnormal case.
Specifically, the server acquires a target time and judges whether the target time is the end time of a first preset time period; and if the target time is the end time of the first preset time period, performing data analysis on the original abnormal case stored in the monitoring pool of the first preset time period according to an abnormal state analysis strategy to obtain a candidate abnormal case.
After the original abnormal case is stored in the monitoring pool in the first preset time period, the server detects and judges the time (target time) in the monitoring pool in the first preset time period in real time, and if the target time is the end time of the first preset time period, the server analyzes the data of the original abnormal case stored in the monitoring pool in the first preset time period according to an abnormal state analysis strategy to obtain a candidate abnormal case, for example: the first preset time period is 10:00-11:00, the target time is 11:00, if the target time is the end time of the first preset time period, a detection task in a timing task mechanism is started (original abnormal cases stored in a monitoring pool of the first preset time period are subjected to data analysis according to an abnormal state analysis strategy to obtain candidate abnormal cases), the running time of the detection task is 20 minutes, and after the running of the detection task is finished, the candidate abnormal cases are stored into the monitoring pool of 11:20-12: 20. By analogy, the same operation steps are adopted for the time judgment and the data analysis of other preset time periods in the preset monitoring pool.
204. Acquiring rule information and case information of a target abnormal case, wherein the rule information is a condition required for terminating the target abnormal case, and the case information is an information element included by the target abnormal case;
specifically, the server acquires the case number and the rule number of the target abnormal case according to the case state of the target abnormal case; sending the case number and the rule number to a preset rule engine, and traversing a preset rule tree through the rule engine to obtain rule information corresponding to the rule number; and generating a key value of the case number through a rule engine and searching a preset case hash table to obtain case information corresponding to the key value.
The server creates a rule tree (i.e., a preset rule tree) in advance and stores case information of the pending task case into a created case hash table (i.e., a preset case hash table). After the server obtains the rule number through a preset rule engine, traversing the rule number of each node in a rule tree established in advance through the rule engine according to the rule number to obtain the corresponding rule number in the nodes of the rule tree and obtain the rule information of the node corresponding to the rule number; after the server obtains the case number through a preset rule engine, a key value of the case number is created, the case hash table is searched through the rule engine according to the key value, the corresponding case number in the case hash table is obtained, and therefore case information corresponding to the case number is obtained.
205. Comparing and analyzing the case information and the rule information, and determining a target information element required for terminating the target abnormal case;
specifically, the server creates a case knowledge graph of case information and a rule knowledge graph of rule information, and randomly walks the case knowledge graph and the rule knowledge graph to obtain a corresponding case information sequence and a corresponding rule information sequence; calculating cosine similarity between the case information sequence and the rule information sequence to obtain a similarity value; and determining the information elements in the case information with the similarity value larger than a preset threshold value as target information elements.
For example: the method comprises the steps of respectively carrying out random walk on a case knowledge graph and a rule knowledge graph to obtain a case information sequence A, a case information sequence B, a rule information sequence A and a rule information sequence B, calculating cosine similarity between the case information sequence A and the rule information sequence A and between the case information sequence A and the rule information sequence B respectively to obtain cosine similarity 1 and cosine similarity 2, calculating case information sequence B and the rule information sequence A and the rule information sequence B respectively to obtain cosine similarity 3 and cosine similarity 4, calculating average values of the cosine similarity 1, the cosine similarity 2, the cosine similarity 3 and the cosine similarity 4 to obtain a final similarity value, subtracting a preset threshold value from the similarity value to obtain a difference value, and taking an information element in case information with the difference value larger than 0 as a target information element. The server compares and analyzes the case information and the rule information through the knowledge graph and the cosine similarity, and the correctness of the target information elements is improved.
206. Generating a visual chart of the target information element according to a preset feedback processing strategy, and rendering the visual chart to a preset display page;
and after the server acquires the preset feedback processing strategy, generating a visual chart of the target information element according to the feedback processing strategy, and rendering the visual chart to a preset display page through a floating window or a display frame. Optionally, the case status corresponding to the target information element and the corresponding position and information of the process node may be added and linked to the visual chart.
207. Judging whether a case processing request based on a visual chart returned by a preset display page is received in a third preset time period;
the server identifies whether the case is processed on the preset display page by the user in the third preset time period by judging whether a case processing request based on the visual chart returned by the preset display page is received in the third preset time period, for example: within 10 minutes (a third preset time period) after the visual chart is fed back to the preset display page, if a user clicks and views the visual chart on the preset display page, the process termination processing is carried out on the corresponding case process node, or the problem or lack data existing in the corresponding case process termination data in the visual chart is filled or selected in the case processing content of the pop-up window, so that a corresponding case processing request based on the visual chart is generated and sent to the server, and the case processing request based on the visual chart indicates that the user refers to the visual chart on the preset display page and carries out corresponding case process operation according to the visual chart.
208. And when a case processing request based on the visual chart returned by the preset display page is not received in a third preset time period, sending the target information element to the user terminal.
When the server does not receive a processing request returned by the preset display page within a third preset time, acquiring a feedback mode, and generating a text or a visual chart corresponding to the feedback mode for the target information element, for example: and if the feedback mode is short message notification, generating content corresponding to the text form by the target information element, sending a case processing request based on the visual chart to the user terminal by the server through the hypertext transfer protocol, and sending the generated text or the visual chart to the user terminal in a feedback mode after receiving the returned hypertext transfer protocol request.
In the embodiment of the invention, on the basis of flexibly responding to the change of the service, monitoring the flow breakpoint data of the pending task case in quasi-real time and feeding back the monitoring result in time and improving the processing efficiency of the flow breakpoint of the pending task case, the target case information is sent to the terminal of the user by judging whether the processing request returned by the preset display page is received in the preset time period, so that the feedback operation of the target case information is reduced, the autonomy of the feedback operation of the target case information is improved, and the processing efficiency of the flow breakpoint of the pending task case is improved.
With reference to fig. 3, the method for processing pending task cases in the embodiment of the present invention is described above, and a processing apparatus for pending task cases in the embodiment of the present invention is described below, where an embodiment of the processing apparatus for pending task cases in the embodiment of the present invention includes:
a first obtaining module 301, configured to obtain a pending task case to be processed, where the pending task case is a case that is located in a target process node but does not terminate a process;
the first data analysis module 302 is configured to perform data analysis on pending task cases according to a preset abnormal state analysis policy to identify original abnormal cases in the pending task cases, and store the original abnormal cases into a preset monitoring pool, where the abnormal state analysis policy is used to analyze whether information of a process node and unprocessed retention time meet preset conditions, and the preset monitoring pool is a plurality of monitoring pools in different preset time periods;
the second data analysis module 303 is configured to perform data analysis on the original abnormal case in the preset monitoring pool according to the abnormal state analysis policy, so as to identify a target abnormal case in the preset monitoring pool;
a second obtaining module 304, configured to obtain rule information and case information of the target abnormal case, where the rule information is a condition required to terminate the target abnormal case, and the case information is an information element included in the target abnormal case;
a comparison analysis module 305, configured to perform comparison analysis on the case information and the rule information, and determine a target information element required for terminating a target abnormal case;
a sending module 306, configured to send the target information element to the user terminal.
In the embodiment of the invention, the pending task case is monitored and judged in real time through the abnormal state analysis strategy, the change of the service can be flexibly responded, the flow breakpoint data of the pending task case is monitored in quasi-real time, the monitoring result is fed back in time, and the processing efficiency of the flow breakpoint of the pending task case is improved.
Referring to FIG. 4, another embodiment of a processing device for pending task cases in accordance with the present invention comprises:
a first obtaining module 301, configured to obtain a pending task case to be processed, where the pending task case is a case that is located in a target process node but does not terminate a process;
the first data analysis module 302 is configured to perform data analysis on pending task cases according to a preset abnormal state analysis policy to identify original abnormal cases in the pending task cases, and store the original abnormal cases into a preset monitoring pool, where the abnormal state analysis policy is used to analyze whether information of a process node and unprocessed retention time meet preset conditions, and the preset monitoring pool is a plurality of monitoring pools in different preset time periods;
the second data analysis module 303 is configured to perform data analysis on the original abnormal case in the preset monitoring pool according to the abnormal state analysis policy, so as to identify a target abnormal case in the preset monitoring pool;
a second obtaining module 304, configured to obtain rule information and case information of the target abnormal case, where the rule information is a condition required to terminate the target abnormal case, and the case information is an information element included in the target abnormal case;
a comparison analysis module 305, configured to perform comparison analysis on the case information and the rule information, and determine a target information element required for terminating a target abnormal case;
a sending module 306, configured to send the target information element to the user terminal;
the sending module 306 specifically includes:
the generating unit 3061 is configured to generate a visualization chart of the target information element according to a preset feedback processing policy, and render the visualization chart to a preset display page;
the judging unit 3062 is configured to judge whether a case processing request based on a visual chart, which is returned by a preset display page, is received in a third preset time period;
a sending unit 3063, configured to send the target information element to the user terminal when a case processing request based on a visual chart returned by the preset display page is not received in a third preset time period.
Optionally, the second data analysis module 303 includes:
the first data analysis unit 3031 is configured to perform data analysis on an original abnormal case stored in the monitoring pool in a first preset time period according to an abnormal state analysis strategy to obtain a candidate abnormal case;
the storage unit 3032 is configured to store the candidate abnormal cases in a monitoring pool in a second preset time period, where a start time of the second preset time period is later than an end time of the first preset time period;
and a second data analysis unit 3033, configured to perform iterative data analysis on the candidate abnormal cases in the monitoring pool in the second preset time period according to the abnormal state analysis policy, so as to obtain a target abnormal case.
Optionally, the first data analysis unit 3031 may further be specifically configured to:
acquiring a target moment, and judging whether the target moment is the end moment of a first preset time period or not;
and if the target time is the end time of the first preset time period, performing data analysis on the original abnormal case stored in the monitoring pool of the first preset time period according to an abnormal state analysis strategy to obtain a candidate abnormal case.
Optionally, the comparative analysis module 305 may be further specifically configured to:
creating a case knowledge map of case information and a rule knowledge map of rule information, and randomly walking the case knowledge map and the rule knowledge map to obtain a corresponding case information sequence and a corresponding rule information sequence;
calculating cosine similarity between the case information sequence and the rule information sequence to obtain a similarity value;
and determining the information elements in the case information with the similarity value larger than a preset threshold value as target information elements.
Optionally, the second obtaining module 304 may be further specifically configured to:
acquiring a case number and a rule number of the target abnormal case according to the case state of the target abnormal case;
sending the case number and the rule number to a preset rule engine, and traversing a preset rule tree through the rule engine to obtain rule information corresponding to the rule number;
and generating a key value of the case number through a rule engine and searching a preset case hash table to obtain case information corresponding to the key value.
Optionally, the processing device of the pending task case may further include:
a setting module 307, configured to acquire pre-stored case information, case number, and case state of a business case that is located at a target process node but does not terminate a process, and set rule information and a feedback processing policy of the business case and a rule number of the rule information through a preset rule engine;
and the creating module 308 is configured to create a corresponding relationship between the case information, the case number, the case status, the rule information, the processing policy, and the rule number, and determine the service case with the corresponding relationship as a pending task case to be processed.
In the embodiment of the invention, on the basis of flexibly responding to the change of the service, monitoring the flow breakpoint data of the pending task case in quasi-real time and feeding back the monitoring result in time and improving the processing efficiency of the flow breakpoint of the pending task case, the target case information is sent to the terminal of the user by judging whether the processing request returned by the preset display page is received in the preset time period, so that the feedback operation of the target case information is reduced, the autonomy of the feedback operation of the target case information is improved, and the processing efficiency of the flow breakpoint of the pending task case is improved.
Fig. 3 and 4 above describe the processing device of the pending task case in the embodiment of the present invention in detail from the perspective of the modular functional entity, and the processing device of the pending task case in the embodiment of the present invention is described in detail from the perspective of hardware processing.
Fig. 5 is a schematic structural diagram of a processing device for a pending task case, where the processing device 500 for the pending task case may have a relatively large difference due to different configurations or performances, and may include one or more processors (CPUs) 510 (e.g., one or more processors) and a memory 520, one or more storage media 530 (e.g., one or more mass storage devices) for storing applications 533 or data 532. Memory 520 and storage media 530 may be, among other things, transient or persistent storage. The program stored on the storage medium 530 may include one or more modules (not shown), each of which may include a sequence of instruction operations for a pending task case processing device 500. Still further, the processor 510 may be configured to communicate with the storage medium 530 to execute a series of instruction operations in the storage medium 530 on the processing device 500 for the pending task case.
The processing device 500 for a pending task case may also include one or more power supplies 540, one or more wired or wireless network interfaces 550, one or more input-output interfaces 560, and/or one or more operating systems 531, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, and the like. Those skilled in the art will appreciate that the pending task case processing device configuration shown in FIG. 5 does not constitute a limitation of the pending task case processing device and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.
The present invention also provides a computer readable storage medium, which may be a non-volatile computer readable storage medium, which may also be a volatile computer readable storage medium, having stored therein instructions, which, when run on a computer, cause the computer to perform the steps of the method of processing the pending task case.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for processing a pending task case, the method for processing the pending task case comprising:
acquiring pending task cases to be processed, wherein the pending task cases are cases which are located in target process nodes but not terminate the processes;
performing data analysis on the pending task cases according to a preset abnormal state analysis strategy to identify original abnormal cases in the pending task cases, and storing the original abnormal cases into a preset monitoring pool, wherein the abnormal state analysis strategy is used for analyzing whether information of process nodes and unprocessed retention time meet preset conditions, and the preset monitoring pool is a plurality of monitoring pools in different preset time periods;
analyzing data of the original abnormal cases in the preset monitoring pool according to the abnormal state analysis strategy so as to identify target abnormal cases in the preset monitoring pool;
acquiring rule information and case information of the target abnormal case, wherein the rule information is a condition required for terminating the target abnormal case, and the case information is an information element included in the target abnormal case;
comparing and analyzing the case information and the rule information, and determining a target information element required for terminating the target abnormal case;
and sending the target information element to a user terminal.
2. The method for handling pending task cases according to claim 1, wherein said analyzing original exception cases in said pre-configured monitoring pool according to said exception status analysis policy to identify target exception cases in said pre-configured monitoring pool comprises:
performing data analysis on the original abnormal cases stored in the monitoring pool in the first preset time period according to the abnormal state analysis strategy to obtain candidate abnormal cases;
storing the candidate abnormal cases in a monitoring pool of a second preset time period, wherein the starting time of the second preset time period is later than the ending time of the first preset time period;
and performing iteration data analysis on the candidate abnormal cases in the monitoring pool in the second preset time period according to the abnormal state analysis strategy to obtain target abnormal cases.
3. The method for handling pending task cases according to claim 2, wherein said analyzing the data of the original abnormal case stored in the monitoring pool for the first preset time period according to said abnormal state analysis policy to obtain the candidate abnormal case comprises:
acquiring a target moment, and judging whether the target moment is the end moment of the first preset time period or not;
and if the target time is the end time of the first preset time period, performing data analysis on the original abnormal case stored in the monitoring pool of the first preset time period according to the abnormal state analysis strategy to obtain a candidate abnormal case.
4. The method for handling pending task cases according to claim 1, wherein said comparing said case information with said rule information to determine the target information elements required to terminate said target exception case comprises:
creating a case knowledge graph of the case information and a rule knowledge graph of the rule information, and carrying out random walk on the case knowledge graph and the rule knowledge graph to obtain a corresponding case information sequence and a corresponding rule information sequence;
calculating cosine similarity between the case information sequence and the rule information sequence to obtain a similarity value;
and determining an information element in the case information with the similarity value larger than a preset threshold value as a target information element, wherein the target information element is stored in a block chain.
5. The method for handling pending task cases according to claim 1, wherein said obtaining rule information and case information of said target exception case comprises:
acquiring the case number and the rule number of the target abnormal case according to the case state of the target abnormal case;
sending the case number and the rule number to a preset rule engine, and traversing a preset rule tree through the rule engine to obtain rule information corresponding to the rule number;
and generating a key value of the case number through the rule engine and retrieving a preset case hash table to obtain case information corresponding to the key value.
6. The method of handling pending task cases according to claim 1, wherein said sending said target information element to a user terminal comprises:
generating a visual chart of the target information element according to a preset feedback processing strategy, and rendering the visual chart to a preset display page;
judging whether a case processing request based on the visual chart returned by the preset display page is received in a third preset time period;
and when a case processing request based on the visual chart returned by the preset display page is not received in a third preset time period, sending the target information element to a user terminal.
7. The method for handling pending task cases according to any of claims 1-6, further comprising, before said obtaining pending task cases to be handled:
acquiring pre-stored case information, case numbers and case states of business cases which are located at target process nodes but not terminate the processes, and setting rule information and feedback processing strategies of the business cases and rule numbers of the rule information through a preset rule engine;
and creating a corresponding relation among the case information, the case number, the case state, the rule information, the processing strategy and the rule number, and determining the business case with the corresponding relation as a pending task case to be processed.
8. A processing apparatus of pending task cases, characterized in that said processing apparatus of pending task cases comprises:
the system comprises a first acquisition module, a second acquisition module and a processing module, wherein the first acquisition module is used for acquiring pending task cases to be processed, and the pending task cases are cases which are located in a target process node but not terminate a process;
the system comprises a first data analysis module, a second data analysis module and a third data analysis module, wherein the first data analysis module is used for carrying out data analysis on the pending task cases according to a preset abnormal state analysis strategy so as to identify original abnormal cases in the pending task cases and store the original abnormal cases into a preset monitoring pool, the abnormal state analysis strategy is used for analyzing whether information of process nodes and unprocessed retention time meet preset conditions, and the preset monitoring pool is a plurality of monitoring pools in different preset time periods;
the second data analysis module is used for carrying out data analysis on the original abnormal cases in the preset monitoring pool according to the abnormal state analysis strategy so as to identify target abnormal cases in the preset monitoring pool;
a second obtaining module, configured to obtain rule information and case information of the target abnormal case, where the rule information is a condition required to terminate the target abnormal case, and the case information is an information element included in the target abnormal case;
the comparison analysis module is used for comparing and analyzing the case information and the rule information and determining a target information element required for terminating the target abnormal case;
and the sending module is used for sending the target information element to the user terminal.
9. A processing device of a pending task case, characterized in that the processing device of a pending task case comprises: a memory having instructions stored therein and at least one processor, the memory and the at least one processor interconnected by a line;
the at least one processor invoking the instructions in the memory to cause the processing device of the pending task case to perform a method of processing the pending task case as recited in any one of claims 1-7.
10. A computer-readable storage medium, having stored thereon a computer program, wherein the computer program, when executed by a processor, implements a method of handling a pending task case according to any of claims 1-7.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112181704A (en) * | 2020-09-28 | 2021-01-05 | 京东数字科技控股股份有限公司 | Big data task processing method and device, electronic equipment and storage medium |
| CN112330308A (en) * | 2021-01-05 | 2021-02-05 | 广州互联网法院 | Case management system and method and electronic device |
| CN112465466A (en) * | 2020-12-10 | 2021-03-09 | 金蝶软件（中国）有限公司 | Flow task execution method and device, computer equipment and storage medium |
| CN113469527A (en) * | 2021-06-30 | 2021-10-01 | 谭颖亮 | Method, system and device for monitoring work flow state and storage medium |
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2020
- 2020-04-28 CN CN202010351230.8A patent/CN111667141A/en active Pending
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112181704A (en) * | 2020-09-28 | 2021-01-05 | 京东数字科技控股股份有限公司 | Big data task processing method and device, electronic equipment and storage medium |
| CN112465466A (en) * | 2020-12-10 | 2021-03-09 | 金蝶软件（中国）有限公司 | Flow task execution method and device, computer equipment and storage medium |
| CN112465466B (en) * | 2020-12-10 | 2024-05-03 | 金蝶软件（中国）有限公司 | Method, device, computer equipment and storage medium for executing flow task |
| CN112330308A (en) * | 2021-01-05 | 2021-02-05 | 广州互联网法院 | Case management system and method and electronic device |
| CN112330308B (en) * | 2021-01-05 | 2021-04-16 | 广州互联网法院 | Case management system and method and electronic device |
| CN113469527A (en) * | 2021-06-30 | 2021-10-01 | 谭颖亮 | Method, system and device for monitoring work flow state and storage medium |
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