CN111309993B - Enterprise asset data portrayal generation method and system - Google Patents
Enterprise asset data portrayal generation method and system Download PDFInfo
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Abstract
The embodiment of the invention provides a method for generating enterprise asset data portraits, which comprises the following steps: acquiring asset representation initial data of a plurality of enterprises, and generating supervision data corresponding to each enterprise according to the asset representation initial data; obtaining enterprise labels of each enterprise and enterprise characteristics of each enterprise according to the supervision data corresponding to each enterprise; acquiring user data of a current supervision account, and acquiring supervision characteristics of the current supervision account according to the user data; obtaining the correlation between the current supervision account and each enterprise according to the supervision characteristics and the enterprise characteristics of each enterprise; and acquiring a target enterprise from the enterprises according to the correlation between the current supervision account number and each enterprise, and outputting a corresponding enterprise asset data portrait according to the enterprise label of the target enterprise. The embodiment of the invention has high efficiency and high accuracy when acquiring the specific information in the enterprise asset data image.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method and a system for generating enterprise asset data portraits.
Background
At present, most enterprise asset management is performed by manually marking enterprise tags, identifying enterprise assets by manually selecting corresponding enterprise tags to generate enterprise asset data portraits for display, wherein the enterprise digital asset portraits can comprise asset data related to enterprise network security, such as vulnerability data, threat/warning data, etc. related to the asset data of an enterprise, law enforcement inspection data, notification data and the like.
Disclosure of Invention
In view of the above, embodiments of the present invention provide a method, a system, a computer device, and a computer readable storage medium for generating an enterprise asset data portrait, which are used for solving the problems of low efficiency and low accuracy when specific information is acquired from an existing enterprise asset data portrait.
The embodiment of the invention solves the technical problems through the following technical scheme:
a method of generating an enterprise asset data representation, comprising:
acquiring asset representation initial data of a plurality of enterprises, and generating supervision data corresponding to each enterprise according to the asset representation initial data;
obtaining enterprise labels of each enterprise according to the supervision data corresponding to each enterprise;
obtaining enterprise characteristics of each enterprise according to the supervision data corresponding to each enterprise;
acquiring user data of a current supervision account, and acquiring supervision characteristics of the current supervision account according to the user data;
obtaining the correlation between the current supervision account and each enterprise according to the supervision characteristics and the enterprise characteristics of each enterprise; a kind of electronic device with high-pressure air-conditioning system
And acquiring a target enterprise from the enterprises according to the current supervision account number and the correlation degree among each enterprise, and outputting a corresponding enterprise asset data portrait according to the enterprise label of the target enterprise.
Optionally, the generating the supervision data corresponding to each enterprise according to the asset representation initial data includes:
acquiring at least one asset representation initial data item and corresponding initial data values of the plurality of enterprises;
normalizing the initial data item and the corresponding data value to obtain a normalized result;
and obtaining the at least one supervision data item and the corresponding supervision data value according to the normalization result.
Optionally, the user data includes administrative user attribute data; the obtaining the user data of the current supervision account, and obtaining the supervision characteristics of the current supervision account according to the user data includes:
acquiring the supervision user attribute data;
a supervisory feature associated with the enterprise feature is extracted from the supervisory user attribute data.
Optionally, the obtaining the user data of the current supervision account, and obtaining the supervision feature of the current supervision account according to the user data includes:
acquiring user input data associated with the current supervision account;
a supervisory feature associated with the enterprise feature is extracted from the user input data.
Optionally, the obtaining the correlation between the current supervision account and each enterprise according to the supervision feature and the enterprise feature of each enterprise includes:
generating a characteristic vector of enterprise characteristics of each enterprise and a characteristic vector of supervision characteristics;
and obtaining a correlation value between each enterprise and the current supervision account through a vector angle cosine algorithm.
Optionally, the number of the target enterprises is a plurality; the obtaining a target enterprise from the plurality of enterprises according to the current supervision account number and the correlation degree between each enterprise, and outputting a corresponding enterprise asset data portrait according to the enterprise tag of the target enterprise, including:
acquiring a plurality of target enterprises according to the correlation value between each enterprise and the current supervision account; a kind of electronic device with high-pressure air-conditioning system
And according to the information of each target enterprise and the enterprise labels of each target enterprise, sequencing according to the relevance values of each target enterprise, and generating and outputting enterprise asset data images corresponding to each target enterprise.
Optionally, the enterprise asset data images corresponding to the target enterprises are sequentially output according to the supervision data values.
In order to achieve the above object, an embodiment of the present invention further provides a system for generating an enterprise asset data representation, including:
the monitoring data generation module is used for acquiring asset representation initial data of a plurality of enterprises and generating monitoring data corresponding to each enterprise according to the asset representation initial data;
the enterprise label generating module is used for obtaining the enterprise label of each enterprise according to the supervision data corresponding to each enterprise;
the enterprise feature acquisition module is used for acquiring enterprise features of each enterprise according to the supervision data corresponding to each enterprise;
the monitoring feature acquisition module is used for acquiring user data of a current monitoring account and acquiring monitoring features of the current monitoring account according to the user data;
the correlation calculation module is used for obtaining the correlation between the current supervision account and each enterprise according to the supervision characteristics and the enterprise characteristics of each enterprise;
and the enterprise asset data portrait generation module is used for acquiring a target enterprise from the enterprises according to the current supervision account number and the correlation degree among each enterprise, and outputting a corresponding enterprise asset data portrait according to the enterprise label of the target enterprise.
To achieve the above object, an embodiment of the present invention further provides a computer apparatus, where the computer apparatus includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor implements the steps of the method for generating an enterprise asset data representation as described above when the computer program is executed.
To achieve the above object, an embodiment of the present invention further provides a computer-readable storage medium having stored therein a computer program executable by at least one processor to cause the at least one processor to perform the steps of the method for generating an enterprise asset data representation as described above.
According to the method, the system, the computer equipment and the computer readable storage medium for generating the enterprise asset data portrait, the supervision data is generated according to the initial data of the enterprise asset portrait, a plurality of enterprise labels are obtained by classifying the supervision data, enterprise labels corresponding to enterprise identifications are obtained according to the supervision data, then the correlation degree of the enterprise and the supervision user is obtained according to the enterprise characteristics and the supervision user characteristics, the enterprise and the enterprise labels corresponding to the enterprise are displayed according to the correlation degree, and when specific information is obtained in the enterprise asset data portrait, the efficiency is high and the accuracy is high.
The invention will now be described in more detail with reference to the drawings and specific examples, which are not intended to limit the invention thereto.
Drawings
FIG. 1 is a schematic view of an application environment according to an embodiment of the present invention;
FIG. 2 is a flow chart of steps in a method for generating an enterprise asset data representation in accordance with a first embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating a specific flow of step S100 in FIG. 2;
FIG. 4 is a schematic diagram illustrating a specific flow of step S400 in FIG. 2;
FIG. 5 is a schematic diagram illustrating another specific flow of step S400 in FIG. 2;
FIG. 6 is a flowchart illustrating the step S500 in FIG. 2;
FIG. 7 is a cosine algorithm formula and schematic diagram;
FIG. 8 is a flowchart illustrating the step S600 in FIG. 2;
FIG. 9 is a schematic program module diagram illustrating a second embodiment of a system for generating an enterprise asset data representation in accordance with the present invention;
FIG. 10 is a diagram showing a hardware configuration of a third embodiment of a computer device according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The technical solutions between the embodiments may be combined with each other, but it is necessary to base the implementation on the basis of those skilled in the art that when the combination of technical solutions contradicts or cannot be implemented, it should be considered that the combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.
Referring to fig. 1, a schematic diagram of an implementation environment of an embodiment of the present invention is shown. The implementation environment comprises: a client 10 and a server 12.
The user terminal 10 is an electronic device with an internet access function, and the device may be a smart phone, a tablet computer, a personal computer, or the like.
The user terminal 10 is provided with an application 11 capable of viewing the enterprise asset data image, and after the user logs in to view the application 11 of the enterprise asset data image through an account number and a password, the user can view the enterprise asset data image.
Server 120 is a server, a cluster of servers, or a cloud computing center. In one possible implementation, server 120 is a background server of application 11 that views enterprise asset data images.
In an alternative embodiment, the server 120 stores initial data of a plurality of enterprises in advance, after a user logs in to the application program 11 for viewing the enterprise asset data image, the server 120 obtains user attribute data, calculates correlation between the supervision account and the enterprise according to the initial data and the user attribute data, and feeds back the corresponding enterprise asset data image to the user terminal 11 according to an instruction input in the application program 11, so that the user views the enterprise asset data image.
Example 1
Referring now to FIG. 2, a flowchart illustrating steps in a method for generating an enterprise asset data representation in accordance with an embodiment of the present invention is shown. It will be appreciated that the flow charts in the method embodiments are not intended to limit the order in which the steps are performed. The following description is exemplary with a computer device as an execution subject, and specifically follows:
step S100: and acquiring asset representation initial data of a plurality of enterprises, and generating supervision data corresponding to each enterprise according to the asset representation initial data.
Specifically, the asset representation initial data of the enterprise includes asset data, vulnerability data, threat/warning data, etc. of the enterprise, law enforcement inspection data, notification data, etc., where the warranty data may be defined as network security information level protection data of the enterprise, and the law enforcement inspection data and notification data may be defined as data of the enterprise after receiving a law enforcement inspection of an administrative institution.
In an exemplary embodiment, as shown in fig. 3, the step S100 may be implemented by:
s101: acquiring at least one asset representation initial data item and corresponding initial data values of the plurality of enterprises;
specifically, at least one initial data item and corresponding initial data value of the asset representation of the enterprise, for example, an asset data item and an asset data value, a vulnerability data item and a vulnerability data value, etc. of the enterprise, and an equal-protection data item and an equal-protection data value, may be obtained, and a combination of two initial data items and corresponding initial data values of the asset representation may be obtained, for example, an asset data item and a vulnerability data item of the enterprise and initial data values corresponding to the two initial data items and the vulnerability data item respectively are obtained.
In an exemplary embodiment, the initial data values for the enterprise are calculated in terms of percentages, i.e., the full score of the initial data value for each initial data item is 100 points. For example, the A enterprise has an initial asset data value of 80 points, an initial vulnerability data value of 60 points, an initial threat/alert data value of 10 points, an equity data value of 60 points, a law enforcement inspection data value of 20 points, and a notification inspection data value of 30 points. In another embodiment, the initial data value of the enterprise may also be calculated according to a tenth system, which is not limited herein.
S102: normalizing the initial data item and the corresponding data value to obtain a normalized result;
specifically, the normalization processing refers to limiting the data to a range after the data is processed, for example, changing the data to a fraction between (0, 1) after the data is processed.
In an exemplary embodiment, the initial data value for enterprise a is normalized to an initial asset data value of 0.31, an initial vulnerability data value of 0.23, an initial threat/alert data value of 0.03, an equity data value of 0.23, a law enforcement inspection data of 0.07, and a notification inspection data of 0.12.
S103: and obtaining the at least one supervision data item and the corresponding supervision data value according to the normalization result.
Specifically, the supervision data item refers to a data item needing to supervise an enterprise, and the supervision data value is a numerical value corresponding to the supervision data item. For example, the enterprise's network security score, report improvement completion rate, compliance check rate, etc. In this embodiment, the supervision data item is obtained by calculating an asset representation initial data item of the enterprise and a corresponding initial data value after normalization processing. For example, the network security score is calculated from the initial asset data value, the initial vulnerability data value, and the initial threat/alert data value of the enterprise, the notification modification completion rate is calculated from the law enforcement check data value and the notification check data value, and the compliance check rate is calculated from the warranty data value. In an exemplary embodiment, when one supervision data item corresponds to a plurality of initial data items, the supervision value is calculated by giving different weights to the initial data items corresponding to the supervision data items; when one supervision data item corresponds to only one initial data item, the data value corresponding to the initial data item is taken as the supervision data value.
For example, the network security score of the enterprise a is calculated by giving the weights of the initial asset data value, the initial vulnerability data value and the initial threat/warning data value of the enterprise 0.4, 0.4 and 0.2 respectively, the notification modification completion rate is calculated by giving the weights of the method check data value and the notification check data value of the enterprise 0.6 and 0.4 respectively, the network security score of the enterprise a is calculated to be 0.22, the notification modification completion rate is 0.09 and the compliance check rate is 0.23.
Step S200: and obtaining enterprise labels of each enterprise according to the supervision data corresponding to each enterprise.
Specifically, the enterprise tag includes: "high risk", "stroke risk", "low risk", "high efficiency", "low efficiency", "recommended", "moderate", "ignore", "alternative", etc. The enterprise labels are obtained by classifying the supervision data, for example, the enterprise labels corresponding to the network security scores are "high risk", "medium risk", "low risk", and when the scores corresponding to the network security scores are within a preset range, for example, 0-0.3 and 0.3-0.6,0.6-1, the enterprise labels are classified as corresponding to the enterprise labels, for example, "high risk", "medium risk", "low risk". When the correction completion rate is notified, or the score corresponding to the compliance inspection rate is within the preset range, the corresponding enterprise labels are classified, for example, the enterprise labels corresponding to the correction completion rate are notified to be "high-efficiency", "low-efficiency", the enterprise labels corresponding to the compliance inspection rate are notified to be "recommended", "moderate", and different enterprise labels correspond to different supervision data ranges. In this embodiment, the mapping relationship is pre-established between the enterprise tag and the supervision data range and stored, and when the supervision data value of the enterprise is obtained by calculation, the supervision data range interval in which the supervision data value of the enterprise is located is determined, and the corresponding enterprise tag is obtained and the enterprise is identified.
Step S300: and obtaining enterprise characteristics of each enterprise according to the supervision data corresponding to each enterprise.
Specifically, the enterprise features refer to features related to extracting enterprise supervision information, such as the above-mentioned enterprise network security score, notify the improvement completion rate, compliance inspection rate, and other features.
Step S400: and acquiring user data of a current supervision account, and acquiring supervision characteristics of the current supervision account according to the user data.
Specifically, the supervision feature refers to a feature related to user data of the supervision account, such as authority of the user when logging in the supervision account, and dimension information input in the interface after the user logs in the supervision account.
In an exemplary embodiment, the user data may include administrative user attribute data; referring to fig. 4, step S400 further includes:
S401A: acquiring supervision user attribute data;
S402A: a supervisory feature associated with the enterprise feature is extracted from the supervisory user attribute data.
In one embodiment, the administrative user attribute data refers to rights (e.g., administrative region, administrative level, administrative content, etc.) when the user logs into the account.
The supervision characteristics associated with the enterprise characteristics can be extracted from the supervision user attribute data, for example, when the authority of the user is a specific authority attribute user, the definition of the authority attribute in the user authority management system comprises a plurality of operation authorities related to network security, the supervision characteristics of the user comprise network security and the like, the definition of the authority attribute in the user authority management system comprises a plurality of operation authorities related to network modification, the supervision characteristics of the user comprise network modification rate and the like, and if the authority of the user is a management account, the user can customize the corresponding management authority in the user authority management system, so that the supervision characteristics associated with the enterprise characteristics can be obtained.
In this embodiment, the supervision feature associated with the enterprise feature is extracted from the supervision user attribute data, and specifically corresponds to the supervision feature associated with the current supervision user about network security score, notifying the improvement completion rate and the compliance inspection rate.
In another embodiment, referring to fig. 5, step S400 further includes:
S401B: acquiring user input data associated with the current supervision account;
S402B: a supervisory feature associated with the enterprise feature is extracted from the user input data.
Specifically, in this embodiment, the user data is user input data of the supervising user after the user logs in the supervising account, for example, the dimension (security score, notification of modification, compliance check, etc.) focused by the user, where, as shown in fig. 6, the user may select the preset dimension on the interface.
Step S500: and obtaining the correlation between the current supervision account and each enterprise according to the supervision characteristics and the enterprise characteristics of each enterprise.
Specifically, the correlation degree between the enterprise and the current account refers to the correlation degree between the enterprise under supervision and the current supervision account. And if the correlation degree is high, the correlation degree between the supervised enterprise and the current supervision account is low.
In an exemplary embodiment, referring to fig. 6, step S500 further includes:
step S501: and generating a characteristic vector of the enterprise characteristics of each enterprise and a characteristic vector of the supervision characteristics.
Specifically, feature vectors corresponding to the features are generated, and feature vectorization is performed according to the value condition of the features.
In an exemplary embodiment, the enterprise feature vector may be represented as a two-dimensional vector C (X1, Y1), where X1 is interpreted as an enterprise network security score and Y1 is interpreted as a notification of a correction completion rate; the vector of regulatory features may be represented as a two-dimensional vector U (X2, Y2), where X2 is interpreted as a value of a regulatory feature associated with the current regulatory user with respect to the network security score and Y2 is interpreted as a value of a regulatory feature associated with the current regulatory user with respect to the notification of the rate of completion of the improvement. The preset association rules of X1 and X2 can be manually selected and checked from a preset database, and association can be automatically established by a machine learning mode through keyword feature extraction and the like.
In another embodiment, the enterprise feature vector may be represented as a three-dimensional vector C (X1, Y1, Z1), where X1 is interpreted as an enterprise network security score, Y1 is interpreted as a notification of a correction completion rate, and Z1 is interpreted as a compliance check rate; the vector of supervisory characteristics may be represented as a three-dimensional vector U (X2, Y2, Z2), where X2 is interpreted as a supervisory characteristic value associated with the current supervisory user with respect to the network security score, Y2 is interpreted as a supervisory characteristic value associated with the current supervisory user with respect to the notification of the improvement completion rate, and Z2 is interpreted as a supervisory characteristic value associated with the current supervisory user with respect to the compliance check rate.
In other embodiments, the feature vectors corresponding to the enterprise and administrative features may be four-dimensional, five-dimensional, or higher-dimensional feature vectors corresponding to enterprise and administrative user features.
Step S502: and obtaining a correlation value between each enterprise and the current supervision account through a vector angle cosine algorithm.
Specifically, the cosine algorithm of the included angle of the vector refers to the cosine value of the included angle of two vectors in a vector space, which is used for measuring the difference between two individuals.
In this embodiment, the cosine value of the vector included angle is the correlation value between each enterprise and the current supervision account. Referring to fig. 7, a specific calculation formula is as follows, the enterprise feature vector is C (X1, Y1), the supervision feature vector is U (X2, Y2), and the enterprise feature vector and the supervision feature vector calculate the correlation between the enterprise feature and the supervision feature by the angle cosine algorithm of the vector as follows:
step S600: and acquiring a target enterprise from the enterprises according to the current supervision account number and the correlation degree among each enterprise, and outputting a corresponding enterprise asset data portrait according to the enterprise label of the target enterprise.
In an exemplary embodiment, the number of the target enterprises is plural, and it should be noted that the number of the plurality of enterprises is greater than or equal to the number of the target enterprises > 0. Referring to fig. 8, step S600 further includes:
step S601: acquiring a plurality of target enterprises according to the correlation value between each enterprise and the current supervision account;
step S602: and according to the information of each target enterprise and the enterprise labels of each target enterprise, sequencing according to the relevance values of each target enterprise, and generating and outputting enterprise asset data images corresponding to each target enterprise.
Specifically, after calculating the correlation value in step S502, the information of each enterprise and the enterprise label corresponding to each enterprise are sequentially output from large to small according to the correlation value.
In an exemplary embodiment, the method for generating an enterprise asset data representation further comprises:
and sequentially outputting enterprise asset data images corresponding to the target enterprises according to the supervision data values.
In another embodiment, when the relevance is calculated according to the dimension focused by the user, the specific information of each enterprise and the enterprise label corresponding to each enterprise are sequentially output according to the size of the supervision data value to generate the enterprise asset data portrait.
For example, the user may select the corresponding supervisory data value option on the operation interface, and when the corresponding supervisory data value option is selected, the specific information of each enterprise and the enterprise label corresponding to each enterprise may be sequentially output according to the size of the corresponding supervisory data value to generate the enterprise asset data representation, so that the user may filter data through various dimensions except the relevance, thereby generating the enterprise asset data representation.
According to the method and the device, the supervision data are generated according to the initial data of the enterprise asset portrait, the supervision data are classified to obtain a plurality of enterprise labels, enterprise labels corresponding to enterprise identifications are obtained according to the supervision data, then the correlation degree of the enterprise and the supervision user is obtained according to the enterprise characteristics and the supervision user characteristics, the enterprise and the enterprise labels corresponding to the enterprise are displayed according to the correlation degree, and when specific information is obtained in the enterprise asset data portrait, the efficiency is high and the accuracy is high.
Example two
With continued reference to FIG. 9, a program module schematic of the enterprise asset data representation generation system of the present invention is shown. In this embodiment, the enterprise asset data representation generation system 20 may include or be partitioned into one or more program modules that are stored in a storage medium and executed by one or more processors to perform the present invention and implement the enterprise asset data representation generation method described above. Program modules depicted in the embodiments of the present invention are directed to a series of computer program instruction segments capable of performing particular functions, and are more suited to describing the execution of the enterprise asset data representation generation system 20 on a storage medium than the program itself. The following description will specifically describe functions of each program module of the present embodiment:
and the supervision data generation module 200 is used for acquiring the asset representation initial data of a plurality of enterprises and generating supervision data corresponding to each enterprise according to the asset representation initial data.
Further, the supervision data generation module 200 is further configured to:
acquiring at least one asset representation initial data item and corresponding initial data values of the plurality of enterprises;
normalizing the initial data item and the corresponding data value to obtain a normalized result;
and obtaining the at least one supervision data item and the corresponding supervision data value according to the normalization result.
And the enterprise tag generating module 202 is configured to obtain an enterprise tag of each enterprise according to the supervision data corresponding to each enterprise.
And the enterprise feature acquisition module 204 is configured to obtain enterprise features of each enterprise according to the supervision data corresponding to each enterprise.
And the supervision characteristic acquisition module 206 is configured to acquire user data of a current supervision account, and obtain supervision characteristics of the current supervision account according to the user data.
Further, the user data includes administrative user attribute data; the supervision feature acquisition module 206 is further configured to: acquiring the supervision user attribute data; a supervisory feature associated with the enterprise feature is extracted from the supervisory user attribute data.
Further, the supervision feature acquisition module 206 is further configured to:
acquiring user input data associated with the current supervision account;
a supervisory feature associated with the enterprise feature is extracted from the user input data.
And the correlation calculation module 208 is configured to obtain a correlation between the current supervision account and each enterprise according to the supervision feature and the enterprise feature of each enterprise.
Further, the correlation calculation module 208 is further configured to:
generating a characteristic vector of enterprise characteristics of each enterprise and a characteristic vector of supervision characteristics;
and obtaining a correlation value between each enterprise and the current supervision account through a vector angle cosine algorithm.
And the enterprise asset data portrait generation module 210 is configured to obtain a target enterprise from the multiple enterprises according to the current supervision account number and the correlation between each enterprise, and output a corresponding enterprise asset data portrait according to an enterprise tag of the target enterprise.
Further, the number of the target enterprises is a plurality; the enterprise asset data representation generation module 210 is further configured to:
acquiring a plurality of target enterprises according to the correlation value between each enterprise and the current supervision account; a kind of electronic device with high-pressure air-conditioning system
And according to the information of each target enterprise and the enterprise labels of each target enterprise, sequencing according to the relevance values of each target enterprise, and generating and outputting enterprise asset data images corresponding to each target enterprise.
Further, the enterprise asset data representation generation module 210 is further configured to:
and sequentially outputting enterprise asset data images corresponding to the target enterprises according to the supervision data values.
Example III
Referring to fig. 10, a hardware architecture diagram of a computer device according to a third embodiment of the present invention is shown. In this embodiment, the computer device 2 is a device capable of automatically performing numerical calculation and/or information processing according to a preset or stored instruction. The computer device 2 may be a rack server, a blade server, a tower server, or a rack server (including a stand-alone server, or a server cluster made up of multiple servers), or the like. As shown in fig. 10, the computer device 2 includes, but is not limited to, at least a memory 21, a processor 22, a network interface 23, and a system 20 for generating representations of enterprise asset data, which are communicatively coupled to each other via a system bus. Wherein:
in this embodiment, the memory 21 includes at least one type of computer-readable storage medium including flash memory, a hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, and the like. In some embodiments, the memory 21 may be an internal storage unit of the computer device 2, such as a hard disk or a memory of the computer device 2. In other embodiments, the memory 21 may also be an external storage device of the computer device 2, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the computer device 2. Of course, the memory 21 may also include both internal storage units of the computer device 2 and external storage devices. In this embodiment, the memory 21 is typically used to store program codes and the like of the operating system and various types of application software installed on the computer device 2, such as the enterprise asset data representation generation system 20 described in the above embodiments. Further, the memory 21 may be used to temporarily store various types of data that have been output or are to be output.
The processor 22 may be a central processing unit (Central Processing Unit, CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments. The processor 22 is typically used to control the overall operation of the computer device 2. In this embodiment, the processor 22 is configured to execute the program code or process data stored in the memory 21, for example, to execute the system 20 for generating an enterprise asset data representation, so as to implement the method for generating an enterprise asset data representation according to the foregoing embodiment.
The network interface 23 may comprise a wireless network interface or a wired network interface, which network interface 23 is typically used for establishing a communication connection between the computer apparatus 2 and other electronic devices. For example, the network interface 23 is used to connect the computer device 2 to an external terminal through a network, establish a data transmission channel and a communication connection between the computer device 2 and the external terminal, and the like. The network may be an Intranet (Intranet), the Internet (Internet), a global system for mobile communications (Global System of Mobile communication, GSM), wideband code division multiple access (Wideband Code Division Multiple Access, WCDMA), a 4G network, a 5G network, bluetooth (Bluetooth), wi-Fi, or other wireless or wired network.
It should be noted that fig. 10 only shows a computer device 2 having components 20-23, but it should be understood that not all of the illustrated components are required to be implemented, and that more or fewer components may be implemented instead.
In this embodiment, the system 20 for generating an enterprise asset data representation stored in the memory 21 may also be divided into one or more program modules, which are stored in the memory 21 and executed by one or more processors (in this embodiment, the processor 22) to complete the present invention.
For example, FIG. 9 illustrates a schematic program module diagram of a second embodiment of the system 20 for generating an enterprise asset data representation, where the system 20 for generating an enterprise asset data representation may be divided into a supervisory data generation module 200, an enterprise tag generation module 202, an enterprise feature acquisition module 204, a supervisory feature acquisition module 206, a relevance computation module 208, and an enterprise asset data representation generation module 210. Program modules depicted herein are directed to a series of computer program instruction segments, which perform particular functions, more readily than programs, for describing the execution of the enterprise asset data representation generation system 20 by the computer device 2. The specific functions of the program module supervision data generating module 200 and the enterprise asset data representation generating module 210 are described in detail in the above embodiments, and are not described herein.
Example IV
The present embodiment also provides a computer-readable storage medium such as a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application store, etc., on which a computer program is stored, which when executed by a processor, performs the corresponding functions. The computer readable storage medium of this embodiment is used to store the system 20 for generating an enterprise asset data representation, which when executed by a processor implements the method for generating an enterprise asset data representation described in the above embodiments.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (9)
1. A method of generating an enterprise asset data representation, comprising:
acquiring asset representation initial data of a plurality of enterprises, and generating supervision data corresponding to each enterprise according to the asset representation initial data;
obtaining enterprise labels of each enterprise according to the supervision data corresponding to each enterprise;
obtaining enterprise characteristics of each enterprise according to the supervision data corresponding to each enterprise;
acquiring user data of a current supervision account, and acquiring supervision characteristics of the current supervision account according to the user data;
obtaining the correlation between the current supervision account and each enterprise according to the supervision characteristics and the enterprise characteristics of each enterprise; a kind of electronic device with high-pressure air-conditioning system
Acquiring target enterprises from the enterprises according to the current supervision account numbers and the correlation degree among the enterprises, and outputting corresponding enterprise asset data portraits according to enterprise labels of the target enterprises;
and obtaining the correlation between the current supervision account and each enterprise according to the supervision characteristics and the enterprise characteristics of each enterprise, including:
generating a characteristic vector of enterprise characteristics of each enterprise and a characteristic vector of supervision characteristics; a kind of electronic device with high-pressure air-conditioning system
And obtaining a correlation value between each enterprise and the current supervision account through a vector angle cosine algorithm.
2. The method of generating an enterprise asset data representation according to claim 1, wherein said generating each enterprise's corresponding administrative data from said asset representation initial data comprises:
acquiring at least one asset representation initial data item and corresponding initial data values of the plurality of enterprises;
normalizing the initial data item and the corresponding data value to obtain a normalized result; a kind of electronic device with high-pressure air-conditioning system
And obtaining the at least one supervision data item and the corresponding supervision data value according to the normalization result.
3. The method of generating an enterprise asset data representation of claim 2, wherein the user data comprises administrative user attribute data;
the obtaining the user data of the current supervision account, and obtaining the supervision characteristics of the current supervision account according to the user data includes:
acquiring the supervision user attribute data; a kind of electronic device with high-pressure air-conditioning system
A supervisory feature associated with the enterprise feature is extracted from the supervisory user attribute data.
4. A method for generating an enterprise asset data representation according to claim 2 or 3, wherein the obtaining the user data of the current supervision account, and obtaining the supervision feature of the current supervision account according to the user data, comprises:
acquiring user input data associated with the current supervision account; a kind of electronic device with high-pressure air-conditioning system
A supervisory feature associated with the enterprise feature is extracted from the user input data.
5. The method of generating an enterprise asset data representation according to claim 2, wherein the number of target enterprises is a plurality of;
the obtaining a target enterprise from the plurality of enterprises according to the current supervision account number and the correlation degree between each enterprise, and outputting a corresponding enterprise asset data portrait according to the enterprise tag of the target enterprise, including:
acquiring a plurality of target enterprises according to the correlation value between each enterprise and the current supervision account; a kind of electronic device with high-pressure air-conditioning system
And according to the information of each target enterprise and the enterprise labels of each target enterprise, sequencing according to the relevance values of each target enterprise, and generating and outputting enterprise asset data images corresponding to each target enterprise.
6. The method of generating an enterprise asset data representation of claim 5, further comprising:
and sequentially outputting enterprise asset data images corresponding to the target enterprises according to the supervision data values.
7. A system for generating representations of enterprise asset data, comprising:
the monitoring data generation module is used for acquiring asset representation initial data of a plurality of enterprises and generating monitoring data corresponding to each enterprise according to the asset representation initial data;
the enterprise label generating module is used for obtaining the enterprise label of each enterprise according to the supervision data corresponding to each enterprise;
the enterprise feature acquisition module is used for acquiring enterprise features of each enterprise according to the supervision data corresponding to each enterprise;
the monitoring feature acquisition module is used for acquiring user data of a current monitoring account and acquiring monitoring features of the current monitoring account according to the user data;
the correlation calculation module is used for obtaining the correlation between the current supervision account and each enterprise according to the supervision characteristics and the enterprise characteristics of each enterprise;
the enterprise asset data portrait generation module is used for acquiring target enterprises from the enterprises according to the current supervision account number and the correlation degree among each enterprise, and outputting corresponding enterprise asset data portraits according to enterprise labels of the target enterprises;
the correlation calculation module is further configured to:
generating a characteristic vector of enterprise characteristics of each enterprise and a characteristic vector of supervision characteristics;
and obtaining a correlation value between each enterprise and the current supervision account through a vector angle cosine algorithm.
8. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of the method of generating an enterprise asset data representation as claimed in any one of claims 1 to 6.
9. A computer-readable storage medium having stored thereon a computer program executable by at least one processor to cause the at least one processor to perform the steps of the method of generating an enterprise asset data representation as claimed in any one of claims 1 to 6.
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