A method, device, equipment and storage medium for determining rules

Abstract

Embodiments of the present invention relate to the field of smart finance, and in particular to a rule determination method, device, equipment and storage medium. The method includes: obtaining organizational information, event information, policy and regulatory information and data resource information; inputting the organizational information, event information, policy and regulatory information and data resource information into a rule determination model to obtain a target rule, wherein the rule determination model is obtained by iteratively training a neural network model with a target sample set. Through the technical solution of the present invention, the problem that the personnel who perform business combing do not understand the basic knowledge of the business field and cannot divide the matters according to the actual business process during the actual business data collection and business process combing process is solved, and the association relationship between organizational information, event information, policy and regulatory information and data resource information can be determined, so that the business combing personnel can intuitively understand the business process relationship.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of computer technology, and in particular, to a rule determination method, apparatus, device, and storage medium. Background Art

[0002] Based on the top-level design reference model of the information public platform and guided by the business reference model, the business sorting and planning methods are used to sort out the business applications carried by the information public platform from the perspective of government functions, services, businesses and matters, and determine the needs of these business applications for data resources, service components and infrastructure, providing a design basis for establishing the information public platform.

[0003] The main combing steps:

[0004] Step 1: Determine the design goals: First, determine the goals of the information public platform design by designing performance evaluation indicators. The information public platform construction performance is evaluated against the information management department, and the business application system construction performance is evaluated against each business department.

[0005] Step 2. Determine business matters: Based on the functional domain, sort out all functions at this level according to the "Three Determination Plan", and refine and classify them layer by layer according to "business domain", "business category", "business line", "business matters" and "business function".

[0006] Step 3: Determine business attributes: Determine business attributes by analyzing service objects, business affiliations, and coverage.

[0007] Step 4: Determine the information resource classification: Based on the business attributes, determine the business system attributes by analyzing the nature of the business, proposing business system security requirements and deployment requirements, etc.

[0008] Step 5. Determine the business system functions: Based on the sorting and determination of business classifications, business attributes and business system attributes, refine the functions of the business system, determine the functions that various application systems should have, and complete the mapping from business functions to system functions.

[0009] Step 6: Determine the classification of information group members; derive the information resource requirements of each business system based on the results of the business system combing; according to the information resource reference model, clarify the information resource providers and exchange methods, information resource users and sharing methods, maintainers and maintenance mechanisms, so as to determine the information resource classification.

[0010] Step 7: Determine the attributes of information resources: clarify the form classification and publicity attributes of information resources.

[0011] Step 8: Determine database attributes: Analyze information resource attributes and design database construction and deployment models.

[0012] Step 9: Determine the data item attributes; design the data item attributes of your department and propose the need to share the data item attributes of other departments.

[0013] Step 10. Determine service resource requirements: Based on the analysis of business system functions and data resources in accordance with the service resource reference model, derive the requirements of each business application for public service resources, including data resources, software technology service resources, and application function service resources.

[0014] Step 11. Determine infrastructure requirements: According to the technical requirements and technical policies in the technical reference model, sort out the infrastructure requirements of various business applications and determine the design requirements for computer rooms, networks, storage backup, security, and operation and maintenance services.

[0015] In step 2, business items are determined by breaking down and classifying the items layer by layer according to "business domain", "business category", "business line", "business items" and "business function". However, in the actual business data collection and business process sorting process, the people who do the business sorting do not understand the basic knowledge of the business field and are unable to form "business domain", "business category", "business line", "business items" and "business function" for the items according to the actual business process.

[0016] Moreover, existing technologies are unable to reflect the upstream and downstream relationships of matters, the superior-subordinate relationships of organizations, the relationships between matters and policies and regulations, and data resources, and business review personnel are unable to intuitively understand the business process relationships. Summary of the invention

[0017] The embodiments of the present invention provide a rule determination method, apparatus, equipment and storage medium, which solve the problem that in the actual business data collection and business process combing process, the personnel performing business combing do not understand the basic knowledge of the business field and cannot form "business domain", "business category", "business line", "business matter" and "business function" for matters according to the actual business process. It can determine the association between organizational information, matter information, policy and regulatory information and data resource information, so that the business combing personnel can intuitively understand the business process relationship.

[0018] In a first aspect, an embodiment of the present invention provides a rule determination method, including:

[0019] Obtain information on organizations, matters, policies and regulations, and data resources;

[0020] The organizational information, event information, policy and regulation information, and data resource information are input into a rule determination model to obtain target rules.

[0021] In a second aspect, an embodiment of the present invention further provides a rule determination device, the device comprising:

[0022] The acquisition module is used to obtain organizational information, event information, policy and regulatory information, and data resource information;

[0023] The determination module is used to input the organizational information, event information, policy and regulation information and data resource information into the rule determination model to obtain the target rules.

[0024] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, any method described in the embodiments of the present invention is implemented.

[0025] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any method described in the embodiments of the present invention.

[0026] In a fifth aspect, an embodiment of the present invention further provides a computer program product, and when the computer program is executed by a processor, the computer program implements any method described in the embodiments of the present invention.

[0027] The embodiment of the present invention obtains organizational information, matter information, policy and regulatory information and data resource information; inputs the organizational information, matter information, policy and regulatory information and data resource information into a rule determination model to obtain a target rule, thereby solving the problem that in the actual business data collection and business process combing process, the personnel performing business combing do not understand the basic knowledge of the business field and cannot form "business domain", "business category", "business line", "business matter" and "business function" for the matters according to the actual business process. The embodiment of the present invention can determine the association relationship between organizational information, matter information, policy and regulatory information and data resource information, so that the business combing personnel can intuitively understand the business process relationship. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0029] Figure 1 is a flow chart of a rule determination method in an embodiment of the present invention;

[0030] Figure 1a is a schematic diagram of a layer structure in an embodiment of the present invention;

[0031] Figure 2 is a schematic diagram of the structure of a rule determination device in an embodiment of the present invention;

[0032] Figure 3 is a schematic structural diagram of an electronic device in an embodiment of the present invention;

[0033] Figure 4 It is a schematic diagram of the structure of a computer-readable storage medium containing a computer program in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only the parts related to the present invention, rather than all structures, are shown in the accompanying drawings. In addition, the embodiments of the present invention and the features in the embodiments may be combined with each other without conflict.

[0035] It should be mentioned before discussing exemplary embodiments in more detail that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe various operations (or steps) as sequential processes, many operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of various operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the accompanying drawings. The process can correspond to methods, functions, procedures, subroutines, subprograms, etc. In addition, the embodiments in the present invention and the features in the embodiments can be combined with each other without conflict.

[0036] The term “including” and its variations used in the present invention are open inclusions, that is, “including but not limited to.” The term “based on” means “based at least in part on.” The term “one embodiment” means “at least one embodiment.”

[0037] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0038] When storing and / or processing the following attribute information, it must comply with relevant national laws and regulations.

[0039] Figure 1A flowchart of a rule determination method provided in an embodiment of the present invention. This embodiment is applicable to rule determination. The method can be executed by a rule determination device in an embodiment of the present invention. The device can be implemented in software and / or hardware. Figure 1 As shown, the method specifically comprises the following steps:

[0040] S110, obtaining organizational information, event information, policy and regulatory information, and data resource information.

[0041] The organizational information includes the full Chinese name of the organization, the Chinese abbreviation of the organization, the organizational responsibilities, the superior organization and the organizational execution cycle, and the upstream and downstream relationships of similar organizations in other provinces or cities are recommended through manual combing or knowledge graphs, and the main business responsibilities of the organization and the superior-subordinate relationships between organizations are manually confirmed. The organizational information is shown in Table 1.

[0042] Table 1

[0043]

[0044] Among them, the matter information includes the executing organization, matter number, matter name, responsible organization, matter validity period, power source, business, matter type, matter level, parent matter, name of generated data resource, system, etc. The matter is associated with the organization through the executing organization and responsible organization in the matter information to clarify the relationship between the organization and the matter, and the relationship between the business system and the matter is clarified through the association between the system and the business system in the matter information. Matter information 1 is shown in Table 2, and matter information 2 is shown in Table 3:

[0045] Table 2

[0046]

[0047] Table 3

[0048]

[0049]

[0050] Among them, policy and regulatory information includes the file name, file number, issuing organization information, implementation date, and information source information of policy documents and laws and regulations. Through policy interpretation, specific clauses are associated with organizational information. The policy and regulatory information is shown in Table 4:

[0051] Table 4

[0052]

[0053]

[0054] The data resource information includes: data resource registration information and data resource item detail information, for example, the data resource information includes: resource name, source item, source system, sharing type, storage repository table and data resource details of the data resource, and the mapping relationship between the data resource and the business system data table field can be reflected through the data resource item details. The data resource registration information is shown in Table 5, and the data resource item detail information is shown in Table 6.

[0055] Table 5

[0056]

[0057] Table 6

[0058]

[0059]

[0060] S120, inputting the organizational information, event information, policy and regulation information and data resource information into a rule determination model to obtain a target rule, wherein the rule determination model is obtained by iteratively training a neural network model with a target sample set.

[0061] Wherein, the rule determination model is obtained by iteratively training the neural network model through the target sample set. Specifically, iteratively training the neural network model through the target sample set includes: establishing a neural network model, inputting the organizational information samples, event information samples, policy and regulatory information samples and data resource information samples in the target sample set into the neural network model to obtain prediction rules; training the parameters of the neural network model according to the objective function formed by the prediction rules and the rule samples corresponding to the organizational information samples, event information samples, policy and regulatory information samples and data resource information samples; returning to execute the operation of inputting the organizational information samples, event information samples, policy and regulatory information samples and data resource information samples in the target sample set into the neural network model to obtain prediction rules, until the rule determination model is obtained.

[0062] Specifically, the information collected by the embodiment of the present invention mainly includes: organizational information, policy and regulation information, event information, application system information, and data resource information. Business sorting personnel can quickly collect business field data through the survey template, and batch import the collected business field data through the embodiment of the present invention, archive and manage the business data imported into the embodiment of the present invention, and use the attribute information of the relevant business survey data as the input of the rule determination model.

[0063] like Figure 1aAs shown, the technical solutions provided by the embodiments of the present invention are mainly divided into three levels:

[0064] 1) Government business resource data collection layer:

[0065] It supports manual information entry and also supports batch import of structured research data using templates, so as to quickly collect business research data and classify and archive the research data according to organizational structure, matters, policies and regulations, and data resources.

[0066] 2) Government business resource data integration layer:

[0067] Based on the input organizational information, matter information, policy and regulatory information, and data resource information, and in accordance with the association rules of "upstream and downstream of matters", "parent-child relationship of matters", and "upstream and downstream of data resources", data integration, data governance, and data analysis operations are performed. Using neural network technology, association points are formed, and a government data model is established to achieve automatic association of different subject contents and form a knowledge graph in the government business field.

[0068] 3) Government affairs knowledge graph application layer:

[0069] Users provide external services based on the formed knowledge graph. The main application scenarios are multi-party data verification, data supply chain, data sub-library application, and government business impact analysis.

[0070] Business combing personnel can achieve rapid business combing through the above three steps, and form business combing deliverables to achieve the goal of rapid delivery.

[0071] In the actual business combing process, enterprises will face high project delivery pressure and high project duplication. Business combing personnel face problems such as many participants, complex business processes, incomplete data collection, incomplete business coverage and non-intuitive business process presentation. As a result, business combing consumes a lot of high-end human resources and the application of data resource platforms fails to achieve the expected results. To solve the above problems, the embodiments of the present invention use a neural network learning algorithm to recommend business assets for new projects based on business assets historically deposited in projects, so as to assist business combing personnel in quickly grasping relevant business information, thereby saving high-end human resources, improving delivery efficiency and achieving the goal of business data asset reuse.

[0072] Optionally, obtaining organizational information, event information, policy and regulatory information, and data resource information includes:

[0073] Get system information;

[0074] The organizational information, event information, policy and regulation information, and data resource information are determined based on the system information.

[0075] The system information includes: the Chinese name of the system, the English name of the system, the system description, the system contractor, the system address, the launch date, the database type and version, the system working time window, the data supply method, the system data start period, the stock data volume, the annual increase data volume, the business contact person, and the contact information. System information 1 is shown in Table 7, and system information 2 is shown in Table 8:

[0076] Table 7

[0077]

[0078] Table 8

[0079]

[0080]

[0081] Optionally, after the organization information, event information, policy and regulation information, and data resource information are input into the rule determination model to obtain the target rule, the method further includes:

[0082] A business panoramic topology map is generated based on the organizational information, event information, policy and regulatory information, data resource information and target rules.

[0083] Specifically, a business panoramic topology map is generated based on the organizational information, matter information, policy and regulatory information, data resource information and target rules. For example, a business panoramic topology map can be generated based on the organizational information, matter information, policy and regulatory information, data resource information, upstream and downstream of matters, parent-child relationships of matters and upstream and downstream of data resources.

[0084] In an example, the collected data is first checked to see whether the data content meets the collection requirements and whether there are any missing items. If there are any data quality issues, feedback is required to the user. Based on the input organizational information, matter information, policy and regulatory information, and data resource information, at least one association rule among "upstream and downstream of matters", "parent-child relationship of matters", and "upstream and downstream of data resources" is obtained. The platform automatically identifies the business process relationships in the business research materials through neural networks, and automatically associates organizations, policies and regulations, matters, and data resources to form a government business knowledge graph.

[0085] Optionally, the target rule includes at least one of: upstream and downstream of matters, parent-child relationship of matters, and upstream and downstream of data resources.

[0086] Optionally, also include:

[0087] When a user's touch operation on the first target item in the business panoramic topology diagram is detected, the upstream and downstream of the first target item, the parent-child relationship of the first target item, the policy and regulatory information related to the first target item, and the organizational structure information related to the first target item are obtained.

[0088] In an example, the data supply chain application scenario can query the association relationship of each item in the business process line and the data supply and demand relationship. In the first step, the system enters key government assets (items, data resources, organizations, policies and regulations, business systems), and generates a business panoramic topology map based on the upstream and downstream relationships of government assets, parent-child relationships, and the mapping relationship between data resources and data tables; in the second step, the user selects the target item in the panoramic map according to business needs; in the third step, the user views the upstream and downstream relationships of the target items in the process, the data resource connection relationship between the target items, policy and regulatory information, and the data supply and demand relationship of each organization according to the required selected business topology map. For example: When there is a problem with the identity information required for handling the medical insurance matter, resulting in the inability to handle the medical insurance business, at this time, according to the data supply chain, the source of the identity information can be traced back, which is convenient for business personnel to trace the data source, rectify the identity information from the source, and improve the efficiency of business handling.

[0089] Optionally, also include:

[0090] Detecting a user's touch operation on a second target item in the business panoramic topology diagram, then acquiring item information corresponding to the second target item;

[0091] Searching the business panorama topology map according to the target item information corresponding to the second target item to obtain the target data resource information corresponding to the target item information;

[0092] The target event information is verified according to the target data resource information.

[0093] The first target item and the second target item may be the same or different, and this is not limited in the embodiment of the present invention.

[0094] It should be noted that the user's touch operation on the first target item in the business panoramic topology map is different from the user's touch operation on the second target item in the business panoramic topology map. For example, if the user single-clicks the target item, it is determined that the user's touch operation is on the first target item in the business panoramic topology map. If the user double-clicks the target item, it is determined that the user's touch operation is on the second target item in the business panoramic topology map.

[0095] Specifically, the method of verifying the target matter information according to the target data resource information can be: determining the first matter information according to the target data resource information, if the first matter information and the target matter information are the same, the verification passes; if the first matter information and the target matter information are different, the verification fails.

[0096] Optionally, verifying the target event information according to the target data resource information includes:

[0097] Determine first item information according to the target data resource information;

[0098] If the first item information and the target item information are the same, the verification is passed;

[0099] If the first item information and the target item information are different, the verification fails.

[0100] In an example, the multi-party data verification application scenario is mainly used for business status information determination. In the first step, the user needs to select a certain item; in the second step, the system will search for the item information corresponding to the selected item, generate data resources for each item in the business topology diagram, and query which data resources have an impact on the item information; in the third step, the system integrates all the data resources that have an impact to help determine the accurate status of government information. Optionally, it also includes:

[0101] Detecting a user's touch operation on a target data resource in the business panoramic topology map, then acquiring a target data table corresponding to the target data resource;

[0102] According to the query information input by the user, the target data table is queried to obtain the target data.

[0103] Among them, the method for obtaining the target data table corresponding to the target data resource can be: query the business panoramic topology map according to the target data resource to obtain the target field that has a mapping relationship with the target data resource; determine the target data table according to the target field. The method for obtaining the target data table corresponding to the target data resource can also be: query the business panoramic topology map to obtain the target matter information corresponding to the target data resource; determine the target system information according to the target matter information; query the target system information according to the target data resource to obtain the target data table corresponding to the target data resource. The method for obtaining the target data table corresponding to the target data resource can also be: query the business panoramic topology map according to the target data resource to obtain the target field that has a mapping relationship with the target data resource and the target matter information corresponding to the target data resource; determine the first data table set according to the target field; determine the target system information according to the target matter information; query the target system information according to the target data resource to obtain the second data table set corresponding to the target data resource; determine the target data table according to the first data table set and the second data table set.

[0104] The query information input by the user is the query information determined by the user according to business requirements, and the embodiment of the present invention does not limit the input method of the query information.

[0105] Optionally, detecting a user's touch operation on a target data resource in the business panoramic topology map, obtaining a target data table corresponding to the target data resource includes:

[0106] When a user touch operation on a target data resource in the business panoramic topology map is detected, the business panoramic topology map is queried according to the target data resource to obtain a target field that has a mapping relationship with the target data resource;

[0107] A target data table is determined according to the target field.

[0108] Among them, the method of querying the business panoramic topology map according to the target data resource to obtain the target field that has a mapping relationship with the target data resource can be: querying the business panoramic topology map according to the target data resource to obtain the target matter information corresponding to the target data resource, determining the target system information according to the target matter information, the target system information includes: the target field that has a mapping relationship with the target data resource, and querying the target system to obtain the target field.

[0109] Optionally, detecting a user's touch operation on a target data resource in the business panoramic topology map, obtaining a target data table corresponding to the target data resource includes:

[0110] When a user touch operation on a target data resource in the business panoramic topology map is detected, the business panoramic topology map is queried to obtain target event information corresponding to the target data resource;

[0111] Determine target system information according to the target event information;

[0112] The target system information is queried according to the target data resource to obtain a target data table corresponding to the target data resource.

[0113] The method of determining the target system information according to the target event information may be: querying a database according to the target event information to obtain the target system information corresponding to the target event information. The database stores the correspondence between event information and system information.

[0114] Specifically, the target system information is queried according to the target data resource to obtain a target data table corresponding to the target data resource. For example, the target system information stores a target data table corresponding to the target data resource. By querying the target system information according to the target data resource, the target data table corresponding to the target data resource can be obtained.

[0115] Optionally, detecting a user's touch operation on a target data resource in the business panoramic topology map, obtaining a target data table corresponding to the target data resource includes:

[0116] When a user touch operation on a target data resource in the business panoramic topology map is detected, the business panoramic topology map is queried according to the target data resource to obtain a target field that has a mapping relationship with the target data resource and target item information corresponding to the target data resource;

[0117] Determine a first data table set according to the target field;

[0118] Determine target system information according to the target event information;

[0119] Query the target system information according to the target data resource to obtain a second data table set corresponding to the target data resource;

[0120] A target data table is determined according to the first data table set and the second data table set.

[0121] The method of determining the target system information according to the target event information may be: querying a database according to the target event information to obtain the target system information corresponding to the target event information. The database stores the correspondence between event information and system information.

[0122] In an example, the data sub-library application recommendation scenario aims to automatically find all data fields that may affect the selected data resource item by combining the front-end business metadata definition and the back-end technical metadata definition for the selected data resource item. The first step is that the user selects a data resource item in the front-end; the second step is that the system searches according to the data resource selected by the user, and queries the target field that has a mapping relationship with the data resource through the mapping relationship between the data resource and the field in the data table, and determines the first data table set according to the target field; the third step is that the system performs a secondary search according to the data resource selected by the user, and queries all the information related to the data resource through the business topology map generated by the system; the fourth step is that the system determines the target system information according to all the information related to the data resource, queries the target system information, and obtains the second data table set; the fifth step is to display the acquisition process of the first data table set and the acquisition process of the second data table set, so that the user can view the acquisition of the data table set; the sixth step is that the user enters the query information according to the actual business needs, queries the target data table, and obtains the target data.

[0123] Optionally, determining a target data table based on the first data table set and the second data table set includes:

[0124] If the data table in the first data table set is the same as the data table in the second data table set, determining the data table in the first data table set or the data table in the second data table set as the target data table;

[0125] If the data tables in the first data table set and the data tables in the second data table set are different, the data tables in the first data table set and the data tables in the second data table set are determined as target data tables.

[0126] Specifically, if the data tables in the first data table set and the data tables in the second data table set are the same, the data tables in the first data table set or the data tables in the second data table set are determined as target data tables. For example, if the first data table set includes: data table 1, data table 2 and data table 3, and the second data table set includes: data table 1, data table 2 and data table 3, since the data tables in the first data table set and the second data table set are the same, data table 1, data table 2 and data table 3 are all determined as target data tables.

[0127] Specifically, if the data tables in the first data table set and the data tables in the second data table set are different, the data tables in the first data table set and the data tables in the second data table set are determined as target data tables. For example, if the first data table set includes: data table 1, data table 2 and data table 3, and the second data table set includes: data table 2, data table 3 and data table 4, since the data tables in the first data table set and the second data table set are different, data table 1, data table 2, data table 3 and data table 4 are all determined as target data tables.

[0128] Optionally, the organizational structure information includes at least one of: organizational name, organizational structure responsibilities, superior organizational structure, and organizational structure execution cycle.

[0129] Optionally, the policy and regulation information includes at least one of: policy and regulation name, policy and regulation number, issuing organization, implementation date and information source.

[0130] Optionally, the matter information includes: the executing organization of the matter, the matter number, the matter name, the responsible organization, the validity period of the matter, the source of authority, the business to which it belongs, the matter type, the matter level, the parent matter, and at least one of the names of the generated data resources.

[0131] Optionally, the data resource information includes at least one of: a data resource name, a source item, a source system, a sharing type, and a data resource description.

[0132] Optionally, also include:

[0133] Detecting a target item of the user in the business panoramic topology map;

[0134] Obtain information on upstream and downstream of target items, parent-child relationships of target items, policy and regulatory information related to target items, and organizational information related to target items.

[0135] Optionally, a rule determination model is obtained by iteratively training a neural network model with a target sample set, including:

[0136] Build a neural network model;

[0137] Inputting the organizational information samples, event information samples, policy and regulation information samples, and data resource information samples in the target sample set into the neural network model to obtain prediction rules;

[0138] Training the parameters of the neural network model according to the objective function formed by the prediction rules and the rule samples corresponding to the organizational information samples, event information samples, policy and regulation information samples, and data resource information samples;

[0139] Return to execute the operation of inputting the organizational information samples, event information samples, policy and regulation information samples and data resource information samples in the target sample set into the neural network model to obtain prediction rules until a rule determination model is obtained.

[0140] Among them, the target sample set can be constructed by: obtaining a large amount of historical data in advance, annotating the historical data, and obtaining the target sample set. For example, it can be to obtain organizational information samples, event information samples, policy and legal information samples, and data resource information samples, and annotate the organizational information samples, event information samples, policy and legal information samples, and data resource information samples with corresponding rules, thereby obtaining the target sample set. In an example, assuming that a certain "event", "data resource", "policy and law" or "application system" is set as an influencing factor, the changes in related factors that can be caused by the change of the influencing factor can be shown based on the business asset management platform. Through the government business asset management platform, business, information, data resources and application systems can be connected to form a multi-layered business and information construction panorama, grasp the overall picture of government business and information construction, guide the orderly advancement of information system construction, and assist government government business reform and smart government construction.

[0141] (1) Topological impact analysis based on events:

[0142] By setting a certain item as an influencing factor, based on the relationship between the item and data resources, application systems and the association rules of "upstream and downstream of items, and parent-child relationship of items", it is possible to predict the impact of changes in the item on other items, data resources, and application systems, and to display the impact areas by category, including "items", "data resources", and "application systems".

[0143] (2) Topological impact analysis based on data resources:

[0144] By setting a certain data resource as an influencing factor, based on the association between data resources and matters, application systems and the association rules of "upstream and downstream data resources", it is possible to predict the impact of changes in the data resource on related data resources, matters, and application systems, and to classify and display the impact areas by "matters", "data resources", and "application systems".

[0145] (3) Topology impact analysis based on application systems:

[0146] By setting a certain application system as an influencing factor, based on the relationship between the application system and matters and data resources, it is possible to predict the impact of changes in the application system on related application systems, data resources and matters, and to display the impact areas by category, namely "matters", "data resources" and "application systems".

[0147] (4) Topological impact analysis based on policies and regulations:

[0148] By setting a certain policy or regulation as an influencing factor, based on the relationship between the policy or regulation and matters, data resources, and the relationship between matters and application systems, it is possible to predict the impact of changes in the policy or regulation on related matters, data resources, and application systems, and to display the impact areas by category, including "matters", "data resources", and "application systems".

[0149] The technical solution of this embodiment obtains organizational information, matter information, policy and regulatory information, and data resource information; inputs the organizational information, matter information, policy and regulatory information, and data resource information into a rule determination model to obtain target rules, thereby solving the problem that in the actual business data collection and business process combing process, the personnel performing business combing do not understand the basic knowledge of the business field and are unable to form "business domain", "business category", "business line", "business matter", and "business function" for the matters according to the actual business process. The technical solution of this embodiment can determine the association relationship between organizational information, matter information, policy and regulatory information, and data resource information, so that the business combing personnel can intuitively understand the business process relationship.

[0150] Figure 2 This is a schematic diagram of the structure of a rule determination device provided by an embodiment of the present invention. This embodiment is applicable to the case of rule determination. The device can be implemented in software and / or hardware. The device can be integrated in any device that provides a rule determination function, such as Figure 2 As shown, the rule determination device specifically includes: an acquisition module 210 and a determination module 220.

[0151] Among them, the acquisition module is used to obtain organizational information, event information, policy and regulatory information, and data resource information;

[0152] The determination module is used to input the organizational information, event information, policy and regulation information and data resource information into the rule determination model to obtain the target rules.

[0153] The above-mentioned product can execute the method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0154] The technical solution of this embodiment obtains organizational information, matter information, policy and regulatory information, and data resource information; inputs the organizational information, matter information, policy and regulatory information, and data resource information into a rule determination model to obtain target rules, thereby solving the problem that in the actual business data collection and business process combing process, the personnel performing business combing do not understand the basic knowledge of the business field and are unable to form "business domain", "business category", "business line", "business matter", and "business function" for the matters according to the actual business process. The technical solution of this embodiment can determine the association relationship between organizational information, matter information, policy and regulatory information, and data resource information, so that the business combing personnel can intuitively understand the business process relationship.

[0155] Figure 3 A schematic diagram of the structure of an electronic device provided in Embodiment 3 of the present invention. Figure 3 A block diagram of an electronic device 312 suitable for implementing embodiments of the present invention is shown. Figure 3 The electronic device 312 shown is only an example and should not limit the functions and scope of use of the embodiments of the present invention. The device 312 is a typical computing device for trajectory fitting functions.

[0156] like Figure 3 As shown, the electronic device 312 is in the form of a general purpose computing device. The components of the electronic device 312 may include, but are not limited to: one or more processors 316, a storage device 328, and a bus 318 connecting different system components (including the storage device 328 and the processor 316).

[0157] Bus 318 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. For example, these architectures include but are not limited to Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus and Peripheral Component Interconnect (PCI) bus.

[0158] The electronic device 312 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 312, including volatile and non-volatile media, removable and non-removable media.

[0159] The storage device 328 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 330 and / or cache memory 332. The electronic device 312 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 334 may be used to read and write non-removable, non-volatile magnetic media ( Figure 3 not shown, usually called a "hard drive"). Although Figure 3 Not shown in the figure, a disk drive for reading and writing a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing a removable non-volatile optical disk (e.g., a read-only optical disk (Compact Disc-Read Only Memory, CD-ROM), a digital video disk (Digital Video Disc-Read Only Memory, DVD-ROM) or other optical media) may be provided. In these cases, each drive may be connected to the bus 318 via one or more data medium interfaces. The storage device 328 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0160] A program 336 having a set (at least one) of program modules 326 may be stored, for example, in a storage device 328, such program modules 326 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 326 generally perform the functions and / or methods of the embodiments described herein.

[0161] The electronic device 312 may also communicate with one or more external devices 314 (e.g., keyboard, pointing device, camera, display 324, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 312, and / or communicate with any device that enables the electronic device 312 to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication may be performed through an input / output (I / O) interface 322. In addition, the electronic device 312 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN) and / or a public network, such as the Internet) through a network adapter 320. As shown, the network adapter 320 communicates with other modules of the electronic device 312 through a bus 318. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 312, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, disk arrays (Redundant Arrays of Independent Disks, RAID) systems, tape drives, and data backup storage systems.

[0162] The processor 316 executes various functional applications and data processing by running the programs stored in the storage device 328, for example, implementing the rule determination method provided in the above embodiment of the present invention:

[0163] Obtain information on organizations, matters, policies and regulations, and data resources;

[0164] The organizational information, event information, policy and regulation information, and data resource information are input into a rule determination model to obtain a target rule, wherein the rule determination model is obtained by iteratively training a neural network model using a target sample set.

[0165] Figure 4 Schematic diagram of the structure of a computer-readable storage medium containing a computer program in an embodiment of the present invention. The embodiment of the present invention provides a computer-readable storage medium 61 on which a computer program 610 is stored. When the program is executed by one or more processors, the rule determination method provided in all the invention embodiments of the present application is implemented:

[0166] Obtain information on organizations, matters, policies and regulations, and data resources;

[0167] The organizational information, event information, policy and regulation information, and data resource information are input into a rule determination model to obtain a target rule, wherein the rule determination model is obtained by iteratively training a neural network model using a target sample set.

[0168] Any combination of one or more computer-readable media can be used. Computer-readable media can be computer-readable signal media or computer-readable storage media or any combination of the above two. Computer-readable storage media can be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: electrical connections with one or more wires, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this document, computer-readable storage media can be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device.

[0169] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0170] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0171] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (Hyper Text Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0172] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0173] Computer program code for performing the operation of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0174] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0175] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the name of a unit does not, in some cases, limit the unit itself.

[0176] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0177] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0178] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A rule determination method, characterized in that: include: Obtain information on organizations, matters, policies and regulations, and data resources; The organizational information includes at least one of the following: the organizational name, organizational structure responsibilities, superior organizational structure, and organizational structure execution cycle; the event information includes at least one of the event execution organization, event number, event name, competent organization, event validity period, power source, affiliated business, event type, event level, parent event, and the name of the generated data resource; the policy and regulation information includes at least one of the policy and regulation name, policy and regulation number, issuing organization, implementation date, and information source; the data resource information includes at least one of the data resource name, source event, source system, sharing type, and data resource description; Input the organizational information, matter information, policy and regulation information and data resource information into a rule determination model to obtain a target rule; wherein the rule determination model is obtained by iteratively training a neural network model with a target sample set; the target rule includes at least one of: upstream and downstream of matters, parent-child relationship of matters, and upstream and downstream of data resources; Generate a business panoramic topology map based on the organizational information, event information, policy and regulatory information, data resource information and target rules; Detecting a user's touch operation on a target data resource in the business panoramic topology map, then acquiring a target data table corresponding to the target data resource; According to the query information input by the user, the target data table is queried to obtain the target data.

2. The method according to claim 1, characterized in that Obtaining organizational information, event information, policy and regulatory information, and data resource information includes: Get system information; The organizational information, event information, policy and regulation information, and data resource information are determined based on the system information.

3. The method according to claim 1, characterized in that Also includes: When a user's touch operation on the first target item in the business panoramic topology diagram is detected, the upstream and downstream of the first target item, the parent-child relationship of the first target item, the policy and regulatory information related to the first target item, and the organizational structure information related to the first target item are obtained.

4. The method according to claim 1, characterized in that Also includes: Detecting a user's touch operation on a second target item in the business panoramic topology diagram, then acquiring item information corresponding to the second target item; Searching the business panorama topology map according to the target item information corresponding to the second target item to obtain the target data resource information corresponding to the target item information; The target event information is verified according to the target data resource information.

5. The method according to claim 4, characterized in that Verifying the target event information according to the target data resource information includes: Determine first item information according to the target data resource information; If the first item information and the target item information are the same, the verification is passed; If the first item information and the target item information are different, the verification fails.

6. The method according to claim 1, characterized in that Detecting a user's touch operation on a target data resource in the business panoramic topology map, obtaining a target data table corresponding to the target data resource includes: When a user touch operation on a target data resource in the business panoramic topology map is detected, the business panoramic topology map is queried according to the target data resource to obtain a target field that has a mapping relationship with the target data resource; A target data table is determined according to the target field.

7. The method according to claim 1, characterized in that Detecting a user's touch operation on a target data resource in the business panoramic topology map, obtaining a target data table corresponding to the target data resource includes: When a user touch operation on a target data resource in the business panoramic topology map is detected, the business panoramic topology map is queried to obtain target event information corresponding to the target data resource; Determine target system information according to the target event information; The target system information is queried according to the target data resource to obtain a target data table corresponding to the target data resource.

8. The method according to claim 1, characterized in that: Detecting a user's touch operation on a target data resource in the business panoramic topology map, obtaining a target data table corresponding to the target data resource includes: When a user touch operation on a target data resource in the business panoramic topology map is detected, the business panoramic topology map is queried according to the target data resource to obtain a target field that has a mapping relationship with the target data resource and target item information corresponding to the target data resource; Determine a first data table set according to the target field; Determine target system information according to the target event information; Query the target system information according to the target data resource to obtain a second data table set corresponding to the target data resource; A target data table is determined according to the first data table set and the second data table set.

9. The method according to claim 8, characterized in that Determining a target data table according to the first data table set and the second data table set includes: If the data table in the first data table set is the same as the data table in the second data table set, determining the data table in the first data table set or the data table in the second data table set as the target data table; If the data tables in the first data table set and the data tables in the second data table set are different, the data tables in the first data table set and the data tables in the second data table set are determined as target data tables.

10. The method according to claim 1, characterized in that The rule determination model is obtained by iteratively training the neural network model with the target sample set, including: Build a neural network model; Inputting the organizational information samples, event information samples, policy and regulation information samples, and data resource information samples in the target sample set into the neural network model to obtain prediction rules; Training the parameters of the neural network model according to the objective function formed by the prediction rules and the rule samples corresponding to the organizational information samples, event information samples, policy and regulation information samples, and data resource information samples; Return to execute the operation of inputting the organizational information samples, event information samples, policy and regulation information samples and data resource information samples in the target sample set into the neural network model to obtain prediction rules until a rule determination model is obtained.

11. A rule determination device, characterized in that: include: The acquisition module is used to obtain organizational information, event information, policy and regulatory information, and data resource information; The organizational information includes at least one of the following: the organizational name, organizational structure responsibilities, superior organizational structure, and organizational structure execution cycle; the event information includes at least one of the event execution organization, event number, event name, competent organization, event validity period, power source, affiliated business, event type, event level, parent event, and the name of the generated data resource; the policy and regulation information includes at least one of the policy and regulation name, policy and regulation number, issuing organization, implementation date, and information source; the data resource information includes at least one of the data resource name, source event, source system, sharing type, and data resource description; Identify modules for: Input the organizational information, matter information, policy and regulation information and data resource information into a rule determination model to obtain a target rule; wherein the rule determination model is obtained by iteratively training a neural network model with a target sample set; the target rule includes at least one of: upstream and downstream of matters, parent-child relationship of matters, and upstream and downstream of data resources; Generate a business panoramic topology map based on the organizational information, event information, policy and regulatory information, data resource information and target rules; Detecting a user's touch operation on a target data resource in the business panoramic topology map, then acquiring a target data table corresponding to the target data resource; According to the query information input by the user, the target data table is queried to obtain the target data.

12. An electronic device, characterized in that: include: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the processors are enabled to implement the method according to any one of claims 1 to 10.

13. A computer-readable storage medium containing a computer program, wherein the computer program is stored thereon, characterized in that: When the program is executed by one or more processors, the method according to any one of claims 1 to 10 is implemented.

14. A computer program product comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 10.

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