CN116842269A

CN116842269A - Policy recommendation method and device based on policy map and electronic equipment

Info

Publication number: CN116842269A
Application number: CN202310874891.2A
Authority: CN
Inventors: 雷云存; 雷佳奇; 植天敏; 扶翰章
Original assignee: Qizhi Technology Co ltd
Current assignee: Qizhi Technology Co ltd
Priority date: 2023-07-17
Filing date: 2023-07-17
Publication date: 2023-10-03

Abstract

A policy recommendation method and device based on a policy map and electronic equipment relate to the technical field of big data. The method comprises the following steps: acquiring policy information input by a user; the policy key information includes a first policy key and a second key; acquiring a first policy map corresponding to the first policy keyword from a preset database according to the first policy keyword; acquiring a second policy map corresponding to the second policy keyword from a preset database according to the second policy keyword; acquiring enterprise data of a user; acquiring a first association degree value of a first policy map and enterprise data, and acquiring a second association degree value of a second policy map and enterprise data; judging the magnitude relation between the first association degree value and the second association degree value, and if the first association degree value is larger than the second association degree value, preferentially displaying the first policy map. By implementing the technical scheme provided by the application, the problem that a user cannot accurately know the adaptation degree of the policy application and the enterprise is solved.

Description

Policy recommendation method and device based on policy map and electronic equipment

Technical Field

The present application relates to the field of software testing technologies, and in particular, to a policy recommendation method and apparatus based on a policy map, and an electronic device.

Background

Nowadays, as the benefits of policies become higher, the application of policies by various enterprises is more and more important, so that the recommendation of policies according to the policy maps becomes a reliable method for recommending policies.

However, the current policy recommendation according to the policy map generally only lists the policy map when the user makes a query, and the user cannot accurately know the adaptation degree of the policy application and the enterprise.

Therefore, there is a need for a policy recommendation method, apparatus and electronic device based on a policy map.

Disclosure of Invention

A policy recommendation method and device based on a policy map and electronic equipment solve the problem that a user cannot accurately know the adaptation degree of a policy application and an enterprise of the user.

In a first aspect of the present application, a policy recommendation method based on a policy map is provided, where the method is applied to a server, and the method specifically includes the following steps: acquiring policy characters input by a user; the policy text includes a plurality of policy keywords; the plurality of policy keywords includes a first policy keyword and a second keyword; the plurality of policy keywords includes a first policy keyword and a second keyword; acquiring a first policy map corresponding to the first policy keyword from a preset database according to the first policy keyword; acquiring a second policy map corresponding to the second policy keyword from a preset database according to the second policy keyword; the preset database is used for storing the corresponding relation of the policy keywords, the policy map and the policy map; acquiring enterprise data of a user; acquiring a first association degree value of a first policy map and enterprise data, and acquiring a second association degree value of a second policy map and enterprise data; judging the magnitude relation between the first association degree value and the second association degree value, and if the first association degree value is larger than the second association degree value, preferentially displaying the first policy map.

Through adopting above-mentioned technical scheme, can be according to a plurality of policy keywords of user input, to the propelling movement of this keyword one-to-one to according to the relevancy of policy map and user's enterprise, decide the propelling movement priority of policy map, on the one hand can make the user know the content of policy map at a glance, on the other hand makes the user can know the application of different policies and self enterprise's adaptation degree accurately through the relation of priority.

Optionally, acquiring policy text data corresponding to the third policy keywords at intervals of preset time; the policy text data may be obtained from a preset website including: policy website release pages in the same region, policy website release pages in the same department and policies belonging to the same important field; acquiring policy information data in association with a third policy keyword in the policy text data; constructing a third policy map corresponding to the third policy key according to the policy information data; constructing a corresponding relation between the third policy keywords and the third policy map, and storing the third policy keywords, the third policy map and the corresponding relation between the third policy keywords and the third policy map into a preset database.

According to the technical scheme, the server updates the policy keywords and the policy maps in the preset library every time a preset time is set, and the updating mode can be that when a new policy keyword is released, the policy keyword is obtained from a corresponding release website, and a corresponding policy map is constructed for the policy keyword, so that the server can timely provide the latest policy recommendation.

Optionally, the policy map includes a plurality of nodes and edges, and the nodes and the edges are connected according to a preset corresponding relationship to form the policy map; wherein; the node is policy information, and the policy information comprises one or more of application conditions, policy names and time limits; the side is side information for representing association information between two policy information.

By adopting the technical scheme, the detailed policy map of a certain policy is constructed by taking the policy information as a node and the association relation of the policy information as a side, so that a user can intuitively know all information associated with the policy.

Optionally, obtaining data to be matched, where the enterprise data includes a plurality of data to be matched; counting the number of matched data through a preset relevancy model; the number of the matched data is the number that the association degree value of the data to be matched and the first policy atlas meets the preset condition, and the number of the matched data is configured to be the first association degree value.

Through the technical scheme, all data in enterprise data, namely data to be matched, are compared with all nodes in a certain policy map one by one, the number of the data to be matched, which meets the preset condition, is counted, the preset relevance model is judged, the number of the data to be matched, which meets the condition, is taken as the relevance value of the policy map, and the server is convenient to judge the priority when recommending the policy map to the user by acquiring the relevance value of each policy map and the enterprise information.

Optionally, acquiring a level of association of the first policy map with the enterprise data; the association class is classified as weak association and strong association; judging the size relation between the number of matched data and a preset threshold value; if the number of the matched data is smaller than a preset threshold value, judging that the association level is weak association; if the number of the matched data is greater than or equal to a preset threshold value, judging that the association level is strong association; the association level is presented to the user.

By adopting the technical scheme, the association degree of the policy patterns and the enterprise information can be displayed to the user by setting the association level, the association level can be divided into two stages, and the judgment is carried out according to the association degree of each policy pattern. It should be noted that, in the present application, the division of the association level may be divided into multiple levels, specifically, the division may be performed according to actual conditions, for example, four preset thresholds may be set from small to large, so that the association level is divided into five levels, which is not limited herein.

Optionally, in response to the operation of clicking the edge by the user, displaying the edge information on the display interface; and responding to the operation of clicking the node by the user, and displaying the node information on a display interface.

Through the technical scheme, the user can check the detailed information of the nodes and the edges in the policy map through clicking operation, so that the user can know the full view of the policy information corresponding to the related policy more clearly.

Optionally, the display page includes a first region and a second region, where the first region is a region displaying a first policy map and a second policy region map; the second area is an area displaying side information and node information.

By the technical scheme, the display area can be divided into two sub-areas, wherein one sub-area is used for displaying the policy map for the user, and the other area is used for displaying the detailed information which the user wants to view. In the present application, the display area may be divided into two or more areas, and for example, the third area may be used to display the above-mentioned association level to the user.

In a second aspect of the present application, there is provided a policy recommendation device based on a policy map, the device being a server, the device comprising an acquisition module and a display module;

The acquisition module is used for acquiring the policy characters input by the user; the policy text includes a plurality of policy keywords; the plurality of policy keywords includes a first policy keyword and a second keyword; according to the first policy keywords, a first policy map corresponding to the first policy keywords is obtained from a preset database; acquiring a second policy map corresponding to the second policy keyword from a preset database according to the second policy keyword; the preset database is used for storing the corresponding relation of the policy keywords, the policy map and the policy map; and acquiring enterprise data of the user; and obtaining a first association value of the first policy map and the enterprise data, and obtaining a second association value of the second policy map and the enterprise data.

And the display module is used for judging the magnitude relation between the first association degree value and the second association degree value, and preferentially displaying the first policy map if the first association degree value is larger than the second association degree value.

Optionally, the acquiring module is configured to acquire policy text data corresponding to the third policy keyword at intervals of a preset time; the policy text data may be obtained from a preset website including: policy website release pages in the same region, policy website release pages in the same department and policies belonging to the same important field; acquiring policy information data in association with a third policy keyword in the policy text data; constructing a third policy map corresponding to the third policy key according to the policy information data; constructing a corresponding relation between the third policy keywords and the third policy map, and storing the third policy keywords, the third policy map and the corresponding relation between the third policy keywords and the third policy map into a preset database.

Optionally, the acquiring module is configured to acquire data to be matched, where the enterprise data includes a plurality of data to be matched; counting the number of matched data through a preset relevancy model; the number of the matched data is the number that the association degree value of the data to be matched and the first policy atlas meets the preset condition, and the number of the matched data is configured to be the first association degree value.

Optionally, the acquiring module is configured to acquire a level of association between the first policy map and the enterprise data; the association class is classified as weak association and strong association; judging the size relation between the number of matched data and a preset threshold value; if the number of the matched data is smaller than a preset threshold value, judging that the association level is weak association; if the number of the matched data is greater than or equal to a preset threshold value, judging that the association level is strong association; the association level is presented to the user.

Optionally, the display module is used for responding to the operation of clicking the edge of the user and displaying the edge information on the display interface; and responding to the operation of clicking the node by the user, and displaying the node information on a display interface.

In a third aspect the application provides an electronic device comprising a processor, a memory for storing instructions, a user interface and a network interface for communicating to other devices, the processor being arranged to execute the instructions stored in the memory to cause the electronic device to perform a method as claimed in any one of the preceding claims.

In a fourth aspect of the application a computer readable storage medium is provided, which stores a computer program for execution by a processor of a method according to any of the preceding claims.

One or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:

1. according to the application, the policy patterns corresponding to the keywords one by one are pushed to the user through the plurality of policy keywords input by the user, and the pushing priority of the policy patterns is determined according to the association degree of the policy patterns and the user enterprise, so that the user can know the content of the policy patterns at a glance, and can accurately know the adaptation degree of applications of different policies and the user enterprise through the priority relation.

2. By setting a preset time, the server updates the policy keywords and the policy maps in the preset library every time a preset time is set, and the updating mode can be that when a new policy keyword is released, the policy keyword is obtained from a corresponding release website, and a corresponding policy map is constructed for the policy keyword, so that the server can timely provide the latest policy recommendation.

3. In the first aspect, the association degree of the policy atlas and the enterprise information can be displayed to the user, the association level can be divided into two levels, and the judgment is carried out according to the association degree of each policy atlas; in the second aspect, the user can check detailed information of nodes and edges in the policy map through clicking operation, so that the user can know the full view of the policy information corresponding to the related policy more clearly; in a third aspect, the display area may be divided into two sub-areas, one of which is used to display a policy map for the user and the other is used to display detailed information that the user wants to view.

Drawings

Fig. 1 is a schematic flow chart of a policy recommendation method based on a policy map according to an embodiment of the present application.

Fig. 2a is a schematic diagram of a policy map according to a policy recommendation method according to an embodiment of the present application.

Fig. 2b is a schematic diagram of another policy map of a policy recommendation method based on a policy map according to an embodiment of the present application.

Fig. 3 is a schematic diagram of a presentation interface of a policy recommendation method based on a policy map according to an embodiment of the present application.

Fig. 4 is a structural diagram of a policy recommendation device based on a policy map according to an embodiment of the present application.

Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Reference numerals illustrate: 41. an acquisition module; 42. a display module; 500. an electronic device; 501. a processor; 502. a memory; 503. a user interface; 504. a network interface; 505. a communication bus.

Detailed Description

In order that those skilled in the art will better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments.

The terminology used in the following embodiments of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification of the present application, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates to the contrary. It should also be understood that the term "and/or" as used in this disclosure refers to and encompasses any or all possible combinations of one or more of the listed items.

The terms "first," "second," and the like, are used below for descriptive purposes only and are not to be construed as implying or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature, and in the description of embodiments of the application, unless otherwise indicated, the meaning of "a plurality" is two or more.

Before describing embodiments of the present application, some terms involved in the embodiments of the present application will be first defined and described.

Service: in the present application, a service refers to an interface set formed by packaging a plurality of interfaces.

In order to make the technical scheme of the present application better understood by those skilled in the art, the present application will be further described in detail with reference to the accompanying drawings.

Referring to fig. 1, a flowchart of a policy recommendation method based on a policy map according to an embodiment of the application is shown, and the method is applied to a server, and the flowchart mainly includes the following steps: s101 to S105.

Step S101, acquiring policy characters input by a user; the policy text includes a plurality of policy keywords; the plurality of policy keywords includes a first policy keyword and a second keyword.

Specifically, the user may input a section of policy text to be queried in the search bar, the policy text may include a plurality of keywords, and the server obtains the policy keywords in the policy information through the policy information input by the user.

For example, the policy words that the user may input are: gao Xin, proprietary new, the policy keyword in the obtained policy information is "high new" and "proprietary new". In the following embodiments, the policy keywords "high new" and "specific new" will be described.

Step S102, according to the first policy keywords, a first policy map corresponding to the first policy keywords is obtained from a preset database; acquiring a second policy map corresponding to the second policy keyword from a preset database according to the second policy keyword; the preset database is used for storing the corresponding relation of the policy keywords, the policy map and the policy map.

Specifically, a preset database is established, and the corresponding policy patterns are queried in the user database through the acquired policy keywords.

Illustrating: inquiring a first policy map corresponding to the policy keyword 'high-new', wherein the policy map is uniquely corresponding to the policy keyword 'high-new'; and inquiring a second policy map corresponding to the policy keyword 'special fine new' in a preset database, wherein the policy map is uniquely corresponding to the policy keyword 'high new'.

In one possible implementation, step S102 further includes: acquiring policy text data corresponding to the third policy keywords at intervals of preset time; the policy text data may be obtained from a preset website including: policy website release pages in the same region, policy website release pages in the same department and policies belonging to the same important field; acquiring policy information data in association with a third policy keyword in the policy text data; constructing a third policy map corresponding to the third policy key according to the policy information data; constructing a corresponding relation between the third policy keywords and the third policy map, and storing the third policy keywords, the third policy map and the corresponding relation between the third policy keywords and the third policy map into a preset database.

Specifically, a preset time is set, and every time the preset time is set, the server obtains new policy keywords through each policy issuing website, and the step can be realized by crawling relevant data from the policy issuing websites through a crawler system. The server extracts the policy information data related to the policy keywords from the related data, constructs the data of the unique corresponding policy patterns of the policy keywords according to the newly acquired policy keywords and the data of the policy information, generates the policy patterns according to the data of the policy patterns, and stores the policy keywords, the policy patterns and the corresponding relations between the policy keywords and the policy patterns in a database for standby. The generation of the policy patterns can be performed through a preset learning model, the preset learning model is trained through a large amount of actual data, and the policy patterns corresponding to different policy keywords can be accurately generated. It should be noted that, in this embodiment, the method for updating the policy keywords further includes another method, when each website changes the information of the policy keywords, the information of the changed policy keywords is obtained, and the corresponding policy map is updated according to the information of the changed policy keywords. Both of the above-mentioned updating methods can implement updating of policy keywords in a preset database, and the present application is not limited herein.

For example, a certain policy text published by a certain policy website is converted into policy data, and the policy data can be determined to be related to a policy keyword "high and new" through a preset training model, then policy information related to "high and new" in the policy data is determined, for example, policy information such as "national high and new technology enterprise", "registration for more than one year", "enterprise innovation ability evaluation requirement" and the like can be extracted through the learning model, and then policy maps of the high and new policy information such as "national high and new technology enterprise", "registration for more than one year", "enterprise innovation ability evaluation requirement" and the like are established.

In one possible implementation, step S102 further includes: the policy map comprises a plurality of nodes and edges, and the nodes and the edges are connected according to a preset corresponding relation to form the policy map; wherein; the node is policy information, and the policy information comprises one or more of application conditions, policy names and time limits; the side is side information for representing association information between two policy information.

Specifically, policy information is taken as a node, and the association relationship of the policy information is taken as a side, so that a detailed policy map of a certain policy is constructed, and a user can intuitively know all information associated with the policy.

Illustrating: referring to fig. 2a, a schematic diagram of a policy map according to a policy recommendation method according to an embodiment of the invention is shown, and a first policy map corresponding to a policy keyword "high and new" is illustrated in fig. 2 a. The edges with the same association relationship may be one or more, for example, in fig. two, the high and new technologies may be used as the starting node, the "name" may be used as the edge information of the first policy map, the "high and new technology enterprise" may be used as the node information of the child node of the first policy map, and the association relationship between the child node "high and new technology enterprise" and the starting node is the "name" relationship; as shown in fig. two, the "region" may be used as the side information of the first policy map, and the "national advanced technology enterprise", "provincial advanced technology enterprise", "municipal advanced technology enterprise" may be used as the node information of the first policy map, so that the association relationship between the sub-node start node "national advanced technology enterprise", "provincial advanced technology enterprise", "municipal advanced technology enterprise" and the start node is the "region" relationship. The sub-node can also establish an association relationship with a lower sub-node, as shown in fig. two, the application condition can be used as the association relationship, the scientific personnel who are registered for more than one year, the scientific personnel who are involved in research and development and related technical innovation activities of the enterprise account for the total number of workers in the same year of the enterprise, the enterprise with the sales income of less than 5,000 ten thousand yuan in the last year, the enterprise with the sales income of less than 5% in the last year, the product (service) income of the last year account for the total income of the enterprise in the same period, the enterprise innovation ability evaluation can meet the corresponding requirement, and the enterprise innovation ability evaluation can be used as the lower sub-node of the national high-technology enterprise.

Step S103, enterprise data of the user are acquired.

Specifically, the enterprise data of the user is data stored locally in the server, and the data may be registration information data input by the user when registering an account, or may be information data manually input to the server by related data of the enterprise searched by related staff through the internet, where the enterprise data includes registration capital of the enterprise, establishment date of the enterprise, administrative penalty record, and the like. The application is not limited to the manner in which the enterprise is obtained.

Step S104, a first association degree value of the first policy map and the enterprise data is obtained, and a second association degree value of the second policy map and the enterprise data is obtained.

Specifically, the association degree judgment of the enterprise data and the node information in the same policy map is carried out in many-to-many mode, so that the association degree value of the enterprise information and the policy map is obtained.

In one possible implementation, step S104 further includes: obtaining data to be matched, wherein the enterprise data comprises a plurality of data to be matched; counting the number of matched data through a preset relevancy model; the number of the matched data is the number that the association degree value of the data to be matched and the first policy atlas meets the preset condition, and the number of the matched data is configured to be the first association degree value.

Specifically, the server inputs enterprise data and a policy map into a preset association degree model, carries out multi-to-many association degree judgment on each enterprise data, namely unmatched data, and each node information in the policy map through the preset association degree model, and when the preset model judges that the association degree of one enterprise data and a single node information in one policy map meets a preset condition, marks the enterprise data as successful pairing, namely the enterprise data is matched data, counts the number of matched data obtained by carrying out association degree judgment on the node information in the same policy map, and takes the number of the matched data as the node information of the policy map.

For example, through a preset relevance model, if it is determined that there are 5 enterprise data in which node information in the enterprise data and the first policy map satisfy a preset relevance condition, the relevance value of the first policy map is taken as the 5 matched enterprise data. It should be noted that, the accuracy of the judgment is improved by a large amount of experimental data, when judging the association degree between a certain enterprise data and a certain node, the judgment standard of the preset association degree model can be defined according to practical situations, for example, the "registration time" in the enterprise data of a certain company, if the association degree calculation is performed on the policy map corresponding to the "high-new" state, the node closest to the "registration time", that is, the node is registered for more than one year, at this time, the preset association degree model can judge whether the "registration time" meets the "registration for more than one year", if yes, the matching is successful, and the enterprise data "registration time" is recorded as matched data.

Step 105, determining a magnitude relation between the first association value and the second association value, and if the first association value is greater than the second association value, preferentially displaying the first policy map.

Specifically, a first association value of the same enterprise data and a first policy map is obtained, a second association value of the same enterprise data and a second policy map is obtained, the magnitude relation of the second association value is compared, and a policy map with a large association value is preferentially displayed to a user.

For example, if it is determined, by the preset relevance model, that there are 5 pieces of enterprise data and the enterprise data whose node information in the first policy map satisfies the preset relevance condition, the 5 pieces of matched enterprise data are used as relevance values of the first policy map, if it is determined that there are 3 pieces of enterprise data whose node information in the enterprise data and the second policy map satisfy the preset relevance condition, the 3 pieces of matched enterprise data are used as relevance values of the second policy map, and the relevance value of the first policy map is greater than the relevance value of the second policy map obtained by comparison, then the first policy map is preferentially displayed to the user. It should be noted that, the user may select to view the second policy map by himself, and may select the second policy map below the first policy map to view on the display page, and then, the user may also select the policy map that the user wants to view between the first policy map and the second policy map, and the server displays the policy map selected by the user. It should be noted that, the second policy map is shown below the first policy map only in one policy map display mode, which is not limited herein.

In one possible implementation, step S105 further includes: acquiring the association level of the first policy map and enterprise data; the association class is classified as weak association and strong association; judging the size relation between the number of matched data and a preset threshold value; if the number of the matched data is smaller than a preset threshold value, judging that the association level is weak association; if the number of the matched data is greater than or equal to a preset threshold value, judging that the association level is strong association; the association level is presented to the user.

Specifically, an association level is set, the association degree of the policy map and the enterprise information can be displayed to the user, the association level can be divided into two levels, and the judgment is carried out according to the association degree of each policy map. It should be noted that, in the present application, the division of the association level may be divided into multiple levels, specifically, the division may be performed according to actual conditions, for example, four preset thresholds may be set from small to large, so that the association level is divided into five levels, which is not limited herein.

For example, 4 preset thresholds may be set and the association level may be classified into 1-5 stars, the 4 preset orders from small to large are 1, 3, 5, 7, and 9, respectively, and if the number of enterprise data satisfying the preset association condition with the node information in the first policy map is α (α is equal to or greater than 0), when α <1, the association level of the enterprise data with the first policy map is 1 star; when 3> alpha is more than or equal to 1, marking the association level of the enterprise data and the first policy map as 2 stars; when the alpha is more than or equal to 5 and is more than or equal to 3, marking the association level of the enterprise data and the first policy map as 3 stars; when the alpha is more than or equal to 7 and is more than or equal to 5, marking the association level of the enterprise data and the first policy map as 4 stars; when 9> alpha is greater than or equal to 7, the association level of the enterprise data with the first policy map is marked as 5 stars. The higher the star rating, the higher the association of the first policy map with the enterprise information.

In one possible implementation, step S105 further includes: responding to the operation of clicking the edge of the user, and displaying the edge information on a display interface; and responding to the operation of clicking the node by the user, and displaying the node information on a display interface.

Specifically, the server can display specific information which the user wants to know according to the operation of the user through the display page.

Taking the node "national high and new technology enterprise" as an example, when a user clicks on the national high and new technology enterprise node, content information related to the "national high and new technology enterprise" is displayed; referring to fig. 2b, another schematic diagram of a policy map based on a policy recommendation method according to an embodiment of the present invention is shown, taking a side "name" as an example, before a user clicks the side, the side information "name" is in a hidden state, i.e. the pre-click state shown in fig. 2b, and after the user clicks the side, the hidden state is cancelled, i.e. the post-click state shown in fig. 2b, and the side information of the side is displayed to the user.

In one possible implementation, step S105 further includes: the display page comprises a first area and a second area, wherein the first area is an area for displaying a first policy map and a second policy area map; the second area is an area displaying side information and node information.

Specifically, by dividing the display area into two sub-areas, one of which is used for displaying a policy map by the user and the other is used for displaying detailed information that the user wants to view. In the present application, the display area may be divided into two or more areas, and for example, the third area may be used to display the above-mentioned association level to the user.

Illustrating: referring to fig. 3, a schematic diagram of a presentation interface of a policy recommendation method based on a policy map according to an embodiment of the application is shown. As shown in fig. 3, in the left part of the display interface, there is a display area of the first policy map and the second policy map; the right upper part of the display interface is a display area for displaying node information or side information in the map after the user clicks the first policy map; the lower right part of the display interface is a presentation part of the association level. The user can also select a second policy map below the first policy map to view, the illustration shows omission information of the second policy map, after the user clicks the second policy map, the server displays detailed information of the second policy map at the current position of the first policy, and the omission information of the first policy map is displayed at the current position of the second policy map, then the user can also select a policy map which the user wants to view between the first policy map and the second policy map, and the server displays the policy map selected by the user.

The application also provides a policy recommendation device based on the policy map, which comprises an acquisition module 41 and a display module 42.

An obtaining module 41, configured to obtain a policy text input by a user; the policy text includes a plurality of policy keywords; the plurality of policy keywords includes a first policy keyword and a second keyword; according to the first policy keywords, a first policy map corresponding to the first policy keywords is obtained from a preset database; acquiring a second policy map corresponding to the second policy keyword from a preset database according to the second policy keyword; the preset database is used for storing the corresponding relation of the policy keywords, the policy map and the policy map; and acquiring enterprise data of the user; and obtaining a first association value of the first policy map and the enterprise data, and obtaining a second association value of the second policy map and the enterprise data.

The display module 42 is configured to determine a magnitude relation between the first association value and the second association value, and if the first association value is greater than the second association value, preferentially display the first policy map.

In a possible implementation manner, the obtaining module 41 is configured to obtain, at intervals of a preset time, policy text data corresponding to the third policy keyword; the policy text data may be obtained from a preset website including: policy website release pages in the same region, policy website release pages in the same department and policies belonging to the same important field; acquiring policy information data in association with a third policy keyword in the policy text data; constructing a third policy map corresponding to the third policy key according to the policy information data; constructing a corresponding relation between the third policy keywords and the third policy map, and storing the third policy keywords, the third policy map and the corresponding relation between the third policy keywords and the third policy map into a preset database.

In one possible implementation, the obtaining module 41 is configured to obtain data to be matched, where the enterprise data includes a plurality of data to be matched; counting the number of matched data through a preset relevancy model; the number of the matched data is the number that the association degree value of the data to be matched and the first policy atlas meets the preset condition, and the number of the matched data is configured to be the first association degree value.

In one possible implementation, the obtaining module 41 is configured to obtain a level of association of the first policy map with the enterprise data; the association class is classified as weak association and strong association; judging the size relation between the number of matched data and a preset threshold value; if the number of the matched data is smaller than a preset threshold value, judging that the association level is weak association; if the number of the matched data is greater than or equal to a preset threshold value, judging that the association level is strong association; the association level is presented to the user.

In one possible implementation, the display module 42 is configured to display side information on the display interface in response to an operation of clicking on the side by the user; and responding to the operation of clicking the node by the user, and displaying the node information on a display interface.

It should be noted that: in the device provided in the above embodiment, when implementing the functions thereof, only the division of the above functional modules is used as an example, in practical application, the above functional allocation may be implemented by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to implement all or part of the functions described above. In addition, the embodiments of the apparatus and the method provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the embodiments of the method are detailed in the method embodiments, which are not repeated herein.

The application also discloses electronic equipment. Referring to fig. 5, fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure. The electronic device 500 may include: at least one processor 501, memory 502, a user interface 503, at least one network interface 504, at least one communication bus 505.

Wherein a communication bus 505 is used to enable the connected communication between these components.

The user interface 503 may include a Display screen (Display) and a Camera (Camera), and the optional user interface 503 may further include a standard wired interface and a standard wireless interface.

The network interface 504 may include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.

Wherein the processor 501 may include one or more processing cores. Processor 501 utilizes various interfaces and lines to connect various portions of the overall recall server, perform various functions of the recall server and process data by executing or executing instructions, programs, code sets, or instruction sets stored in memory 502, and invoking data stored in memory 502. Alternatively, the processor 501 may be implemented in hardware in at least one of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), programmable logic array (Programmable Logic Array, PLA). The processor 501 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), and a modem, etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 501 and may be implemented by a single chip.

The Memory 502 may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 502 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). Memory 502 may be used to store instructions, programs, code sets, or instruction sets. The memory 502 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-described various method embodiments, etc.; the storage data area may store data or the like involved in the above respective method embodiments. The memory 502 may also be at least one storage device located remotely from the aforementioned processor 501. Referring to fig. 5, an operating system, a network communication module, a user interface module, and a policy recommendation application based on a policy profile may be included in memory 502, which is a computer storage medium.

In the electronic device 500 shown in fig. 5, the user interface 503 is mainly used for providing an input interface for a user, and acquiring data input by the user; and processor 501 may be configured to invoke a policy recommendation application stored in memory 502 that, when executed by one or more processors 501, causes electronic device 500 to perform the method as described in one or more of the embodiments above. It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present application is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all of the preferred embodiments, and that the acts and modules referred to are not necessarily required for the present application.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, such as a division of units, merely a division of logic functions, and there may be additional divisions in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some service interface, device or unit indirect coupling or communication connection, electrical or otherwise.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be embodied essentially or partly in the form of a software product, or all or part of the technical solution, which is stored in a memory, and includes several instructions for causing a computer device (which may be a personal computer, a recall server, or a network device, etc.) to perform all or part of the steps of the method of the embodiments of the present application. And the aforementioned memory includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a magnetic disk or an optical disk.

As used in the above embodiments, the term "when …" may be interpreted to mean "if …" or "after …" or "in response to determination …" or "in response to detection …" depending on the context. Similarly, the phrase "at the time of determination …" or "if detected (a stated condition or event)" may be interpreted to mean "if determined …" or "in response to determination …" or "at the time of detection (a stated condition or event)" or "in response to detection (a stated condition or event)" depending on the context.

In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present application, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website, computer, recall server, or data center to another website, computer, recall server, or data center by wired (e.g., coaxial cable, fiber optic, digital subscriber line), or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device including one or more recall servers, data centers, etc. that can be integrated with the available medium. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk), etc.

Those of ordinary skill in the art will appreciate that implementing all or part of the above-described method embodiments may be accomplished by a computer program to instruct related hardware, the program may be stored in a computer readable storage medium, and the program may include the above-described method embodiments when executed. And the aforementioned storage medium includes: ROM or random access memory RAM, magnetic or optical disk, etc.

The above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application 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 scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the application.

Claims

1. A policy recommendation method based on a policy profile, the method being applied to a server, the method comprising:

acquiring policy characters input by a user; the policy text comprises a plurality of policy keywords; the plurality of policy keywords includes a first policy keyword and a second keyword;

Acquiring a first policy map corresponding to the first policy keyword from a preset database according to the first policy keyword; acquiring a second policy map corresponding to the second policy keyword from the preset database according to the second policy keyword; the preset database is used for storing a policy keyword, a policy map and a corresponding relation between the policy keyword and the policy map;

acquiring enterprise data of the user;

acquiring a first association degree value of the first policy map and the enterprise data, and acquiring a second association degree value of the second policy map and the enterprise data;

judging the magnitude relation between the first association degree value and the second association degree value, and if the first association degree value is larger than the second association degree value, preferentially displaying the first policy map.

2. The method according to claim 1, wherein a first policy map corresponding to the first policy keyword is obtained in a preset database according to the first policy keyword; according to the second policy keywords, before obtaining a second policy map corresponding to the second policy keywords in the preset database, the method further includes:

Acquiring policy text data corresponding to the third policy keywords at intervals of preset time; the policy text data may be obtained from a preset website comprising: policy website release pages in the same region, policy website release pages in the same department and policies belonging to the same important field;

acquiring policy information data in the policy text data, wherein the policy information data has an association relationship with the third policy keywords;

constructing a third policy map corresponding to the third policy key according to the policy information data;

constructing a corresponding relation between the third policy keywords and a third policy map, and storing the third policy keywords, the third policy map and the corresponding relation between the third policy keywords and the third policy map into the preset database.

3. The method of claim 2, wherein the policy map comprises a plurality of nodes and edges, the nodes and edges being connected according to a predetermined correspondence to form the policy map; wherein;

the node is the policy information, and the policy information comprises one or more of application conditions, policy names and time limits;

The side is side information for representing association information between two of the policy information.

4. The method according to claim 1, wherein the obtaining a first association value between the first policy map and the enterprise data specifically comprises:

obtaining data to be matched, wherein the enterprise data comprises a plurality of data to be matched;

counting the number of matched data through a preset relevancy model; the number of the matched data is the number that the association degree value of the data to be matched and the first policy map meets a preset condition, and the number of the matched data is configured to be the first association degree value.

5. The method of claim 4, wherein after the determining the magnitude relation between the first association value and the second association value, if the first association value is greater than the second association value, the first policy map is preferentially displayed, the method further comprises:

acquiring a level of association of the first policy map with the enterprise data; the association class is classified as weak association and strong association;

judging the size relation between the number of the matched data and a preset threshold value;

If the number of the matched data is smaller than the preset threshold, judging the association level as the weak association;

if the number of the matched data is greater than or equal to the preset threshold value, judging that the association level is the strong association;

the association level is presented to the user.

6. The method of claim 3, wherein after said determining the magnitude relation between the first association value and the second association value, if the first association value is greater than the second association value, the method further comprises:

responding to the operation of clicking the edge by the user, and displaying the edge information on a display interface;

and responding to the operation of clicking the node by the user, and displaying the node information on the display interface.

7. The method of claim 6, wherein the presentation interface comprises a first region and a second region, the first region being a region in which the first policy map and the second policy region map are presented;

the second area is an area displaying the side information and the node information.

8. A policy recommendation device based on a policy map is characterized in that the device is a server and comprises an acquisition module (41) and a display module (42),

the acquisition module (41) is used for acquiring policy information input by a user; the policy information includes a plurality of policy keywords; the plurality of policy keywords includes a first policy keyword and a second policy keyword; according to the first policy keywords, a first policy map corresponding to the first policy keywords is obtained from a preset database; acquiring a second policy map corresponding to the second policy keyword from the preset database according to the second policy keyword; the preset database is used for storing a policy keyword, a policy map and a corresponding relation between the policy keyword and the policy map; and, obtaining enterprise data of the user; and obtaining a first association value of the first policy map with the enterprise data, and obtaining a second association value of the second policy map with the enterprise data;

the display module (42) is configured to determine a magnitude relation between the first association value and the second association value, and if the first association value is greater than the second association value, preferentially display the first policy map.

9. An electronic device comprising a processor (501), a memory (502), a user interface (503) and a network interface (504), the memory (502) being configured to store instructions, the user interface (503) and the network interface (504) being configured to communicate to other devices, the processor (501) being configured to execute the instructions stored in the memory (502) to cause the electronic device (500) to perform the method according to any one of claims 1 to 7.

10. A computer readable storage medium storing instructions which, when executed, perform the method steps of any one of claims 1 to 7.