CN113392224A - Method and system for constructing formation information knowledge graph - Google Patents
Method and system for constructing formation information knowledge graph Download PDFInfo
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Abstract
The invention relates to a method and a system for constructing a formation information knowledge graph, wherein the method comprises the following steps: 1) based on actual working business logic, system information is combed, and a structural entity relationship model of a system map is designed; 2) collecting a data source, preprocessing the data source, and identifying entity information; 3) constructing an entity-relation-entity triple structure based on the identified entity information, and performing data conversion on the structure based on a data structure model to complete the technical construction of a system map; 4) and developing a system map function module by combining a knowledge life cycle principle and an actual application scene, and completing construction of an application layer of the system map. Compared with the prior art, the method has the advantages of reducing labor cost, improving system information query efficiency and the like.
Description
Technical Field
The invention relates to the fields of knowledge maps, scene understanding and information retrieval, in particular to a method and a system for constructing a manufacturing information knowledge map.
Background
In recent years, in order to adapt to the rapid development of the financial market in the information technology age, effectively control and avoid financial risks from causing adverse effects on social economy, internal control management of financial enterprises has been greatly developed under the dual driving force of external audit supervision and enterprise development. The establishment of corresponding system standard aiming at various work flows or fields is one of important measures for constructing and perfecting internal control framework of financial enterprises, but in the face of the increasing scale of internal system of financial enterprises, the currently generally adopted text archive management mode is difficult to support the system information management requirement of continuous development of enterprises, and the main pain points can be summarized as the following two points:
(1) the manual carding system has the advantages of standard mass system, high cost, low efficiency and difficult maintenance
Along with the cross-domain expansion of financial services and the deep fusion of the financial services and technologies, the internal organization structure of an enterprise is promoted to change, the cross-domain and cross-function interaction and cooperation of work flows are continuously increased, the complexity is continuously improved, the standard quantity and types of related systems are also continuously increased, the incidence relation and the constraint relation are also complicated and complicated, the work flows are heavy day by day, the system is overstaffed, and the overall operation efficiency of the enterprise is influenced. The text archive management mode cannot intuitively provide the incidence relation information between the process systems, and a large amount of labor cost is required to be invested to screen, classify and comb the massive system information, so that the difficulty of developing scientific and technological governance and optimizing the process systems of enterprises is greatly increased.
(2) The natural organization form of system information is relatively original, systematic logic association and deep integration are lacked among the information, and the information searching and obtaining efficiency is low
The establishment and the update of the internal control system of the financial enterprise are usually guided by solving the actual working problem, meeting the compliance requirements and the like, certain hysteresis often exists, and global planning is lacked. Under the mode of text archive management, various system information is relatively dispersed, and the mutual incidence relation is not transparent, so that the system information is integrated, shared and inquired at low efficiency, the accuracy and integrity depend on the degree of understanding of an information inquirer on a system, and the threshold of popularization of system specification in enterprises is improved to a certain extent, and the difficulty of system implementation is increased.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a method and a system for constructing a system information knowledge graph, which fully identify the incidence relation among different entities by disassembling system texts, completely and quickly present a retrieval result in a graphical mode and greatly improve the retrieval efficiency.
The purpose of the invention can be realized by the following technical scheme:
a method for constructing a formation information knowledge graph comprises the following steps:
s1: and designing a structural entity relation model of a system map based on actual working business logic, system information combing and system information.
S2: collecting a data source, preprocessing the data source through a marking platform, identifying information in system documents in the data source into different entities, searching the relevance among the entities according to an actual working flow, and designing a data structure model by combining an entity relation model of a system map.
S3: and constructing an entity-relation-entity triple structure, and performing data conversion on the structure based on a data structure model to complete the technical construction of the system map.
S4: and developing a system map function module by combining a knowledge life cycle principle and an actual application scene, and completing construction of an application layer of the system map.
Step S3 specifically includes the following steps:
31) the method comprises the steps of fusing a data source, extracting and storing standardized data objects from the data source, mapping the standardized data objects into an entity relationship group, and forming entity-relationship-entity triple structure data by combining identified entities and entity relationships based on the entity relationship group;
32) and converting the unstructured triple structure data into structured data, designing related algorithm logic, and completing technical layer construction of a system map.
The invention also relates to a system for constructing the formation information knowledge graph, which comprises the following components:
and the preprocessing module is used for understanding the initial system file through natural language, extracting entities according to a preset rule and arranging and forming triple information according to the relationship between the entities.
And the application service module provides a function query interface, realizes information interaction with the data layer and the front-end page through the interface, receives data transmitted by the preprocessing module, and inputs the fused information into the graph database to form a knowledge graph of system information.
And the data layer stores the text information, the entity basic information and the relationship between the entities by adopting a relational database and a graph database.
And the front-end page is used for realizing image drawing and UI display, converting the user input into a request and sending the request to the back-end server.
And the back-end server realizes data interaction with the data layer and responds to the request sent by the front-end page.
Further, the front end page employs a VUE frame. The back-end server adopts a Springboot frame.
Further, the graph database of the data layer adopts a Neo4j database, and the relational database adopts an Oracle database.
The user inputs a query condition, the Element-UI triggers a relevant event according to the input of the user, sends a request to the back-end server through Axios, updates entity relation data to a D3.js drawing map after acquiring a query result from the relational database, updates entity detail data to the Element-UI to display the query result, and the back-end server realizes entity relation data interaction with the Neo4j database, realizes entity detail data interaction with the Oracle database and responds to the request of the Axios.
Further, the back-end server realizes entity relationship data interaction with the Neo4j database through an API (application programming interface).
Further, the back-end server realizes entity detail data interaction with an Oracle database through an API (application programming interface).
Compared with the prior art, the system information knowledge graph construction method and the system provided by the invention at least have the following beneficial effects:
1) by means of the technical advantages of relational network searching of a graph database, system information and relational atlas query efficiency are greatly improved, more comprehensive and accurate system information is provided in a point-to-surface mode, and manual carding, screening and communication costs invested by financial enterprises for acquiring or sharing system standard information can be effectively reduced.
2) A user can quickly acquire a workflow system map to be known by inputting query information (including keywords, specified problems and the like), and compared with the conventional matching query of the keywords of the document content, the system information query efficiency is obviously improved, the query result accuracy and integrity are obviously improved, and the manual workload of information screening is reduced.
Drawings
FIG. 1 is a schematic diagram of the principal principles of a system information knowledge-graph construction method in an embodiment;
FIG. 2 is a schematic diagram of the main structure of the system information knowledge-graph construction system in the embodiment;
FIG. 3 is a schematic diagram of a framework principle of the system for constructing an institutional information knowledge graph in the embodiment.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, shall fall within the scope of protection of the present invention.
Examples
The invention provides a method for constructing a formation information knowledge graph, which mainly comprises the following operation steps in actual use:
step 1, based on the business logic of the actual work, combing system information and designing a structural entity relationship model of a system map.
And 2, collecting data sources and preprocessing the data sources through a marking platform. Identifying the work items, work products and the like in the system documents as entities, and finding out the relevance among the entities according to the actual workflow.
And 3, designing a data structure model by combining the entity relationship model.
And 4, extracting system information in the data source and mapping the system information into an entity relationship group to form an entity-relationship-entity triple structure. And converting the unstructured data into structured data, designing related algorithm logic, and completing the technical layer construction of the system map.
And 5, developing a system map function module by combining the knowledge life cycle principle and the practical application scene, and completing construction of an application layer of the system map.
Specifically, the method of the present invention implements processing and management of system information based on a technical layer and an application layer, as shown in fig. 1, wherein the technical layer mainly performs three-stage data processing steps, and the application layer is configured to perform modular application on a processing procedure performed by the technical layer and perform system information management on data processed by the technical layer.
The technical layer three-stage data processing process comprises the following steps: text semantic understanding, data conversion and storage, and system map calculation and application.
The main content of the text semantic understanding step is to execute the modeling of the structured system information, namely, the original system document is preprocessed on the basis of a marking platform at first, the structured system information is extracted, and the entity identification and the entity relationship identification are carried out on the structured system information after the extraction. And inputting the identified data into a data conversion and storage step.
The main content of the data conversion and storage steps is to construct a system information knowledge base. Specifically, the method comprises the steps of firstly fusing a data source, extracting and storing standardized data objects from the data source, mapping the standardized data objects into an entity relationship group, and forming entity-relationship-entity triple structure data by combining identified entities and entity relationships based on the entity relationship group. And then converting the unstructured data into structured data, designing related algorithm logic, and completing technical layer construction of a system map.
The system level map calculation and application steps mainly comprise the steps of constructing a system information relation map, firstly calculating a system information association path according to an entity relation group, analyzing system information retrieval and logic, developing system map function module development by combining a knowledge life cycle principle and an actual application scene, completing the construction of an application layer of the system map, and further being used for realizing the construction and efficient query of a system information relation network by the application layer based on a map database technology.
After the technical layer finishes data processing, the application layer executes system management based on the constructed system map, and is provided with a plurality of modules and corresponding interfaces, and the application layer mainly comprises the following modules:
and the system specification importing module is used for importing a system specification file.
And the system information identification module is used for identifying system information of the imported system standard file.
And (5) building a relation graph, and executing a relation graph building process in the technical layer.
And dynamically displaying a system graph, namely dynamically displaying the constructed relation graph, specifically, storing entity information as nodes and relations between entities as edges into a knowledge graph according to the triple structure data, and generating a visual interface for a user to inquire information.
The application layer also comprises other functional modules, including a system chart intelligent retrieval module for providing a work flow, a supervision contract audit chart intelligent retrieval module, a system information identification strategy management module, a system information dynamic maintenance management module, an application authority management module, a system information error correction module, a supplement feedback channel module, a system information sharing management module and the like. All modules are realized by executing information interaction through a system information relationship network constructed based on a graph database technology.
The invention also provides a system for constructing the formation information knowledge graph, which comprises a preprocessing module, and a data layer, an application service module, a front-end page and a back-end server which are sequentially connected. The preprocessing module is connected with the application service module.
And the preprocessing module is used for understanding the initial system file through natural language, extracting entities according to preset rules, such as working fields, use frequency and the like, and arranging and forming the triple information according to the relationship among the entities.
The application service module comprises various inquiry interfaces and provides functions such as authority authentication, document editing, information import and the like. The information interaction is realized through the interface, the data layer and the front-end page, the input result interaction is carried out between the application service module and the front-end page, the node information and the relation information interaction are carried out between the application service module and the data layer, and the application service module receives data transmitted by the preprocessing module, namely triple information processed by the preprocessing module is input into the data layer or the front-end page through the interface provided by the application service module. And the application service module fuses the acquired information and inputs the fused information into the graph database to form a knowledge graph of system information.
And the data layer adopts a relational database and a graph database and is used for storing large-segment text information, storing entity basic information and the relationship between entities. Preferably, the graph database is a Neo4j database, and the relational database is an Oracle database.
The front-end page mainly realizes image drawing and UI display, converts user input into a request and sends the request to the back-end server. Specifically, the front-end page generally adopts a VUE frame, and components such as ElementUI, Axios, D3.js and the like are introduced to realize functions such as data display, request initiation, image drawing and the like.
The back-end server adopts a Springboot framework. The user inputs a query condition, the Element-UI triggers a relevant event according to the input of the user, sends a request to the back end through Axios, updates entity relation data to a D3.js drawing map after acquiring a query result from the relational database, and updates entity detail data to the Element-UI to display the query result, as shown in FIG. 3. And the back-end server realizes entity relation data interaction with the Neo4j database through an API (application programming interface) interface, realizes entity detail data interaction with the Oracle database, and responds to the request of Axios through the API interface.
By means of the technical advantages of relational network searching of the graph database, the system information and the relational graph thereof are greatly improved, more comprehensive and accurate system information is provided in a point-to-surface mode, and the manual carding, screening and communication cost invested by financial enterprises for acquiring or sharing system standard information can be effectively reduced. The user can quickly acquire the workflow system graph to be known by inputting query information (including keywords, specified problems and the like), and compared with the conventional matching query of the keywords of the document content, the system information query efficiency is obviously improved, the query result accuracy and integrity are obviously improved, the manual workload of information screening is reduced, and convenience can be provided in the following scenes: 1) the work flow system is standard, self-learning and internal training; 2) a workflow executor needs to know which workflows have relevance and dependency (such as upstream and downstream flows, interactive flows and the like) with the workflow and system specification information of the workflows; 3) when a worker in charge of the workflow carries out the workflow optimization, the worker needs to know which system specifications should be followed or revised by the workflow, and to evaluate the influence range of the revision of the workflow specifications.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and those skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A method for constructing a formation information knowledge graph is characterized by comprising the following steps:
1) based on actual working business logic, system information is combed, and a structural entity relationship model of a system map is designed;
2) collecting a data source, preprocessing the data source, and identifying entity information;
3) constructing an entity-relation-entity triple structure based on the identified entity information, and performing data conversion on the structure based on a data structure model to complete the technical construction of a system map;
4) and developing a system map function module by combining a knowledge life cycle principle and an actual application scene, and completing construction of an application layer of the system map.
2. The system information knowledge graph construction method according to claim 1, wherein in the step 2), the specific content of the step 2) is as follows:
collecting a data source, preprocessing the data source through a marking platform, identifying different entities from information in system documents in the data source, searching the relevance among the entities according to an actual work flow, and designing a data structure model by combining an entity relation model of a system map.
3. The system information knowledge graph construction method according to claim 2, wherein the step 3) specifically comprises the following steps:
31) the method comprises the steps of fusing a data source, extracting and storing standardized data objects from the data source, mapping the standardized data objects into an entity relationship group, and forming entity-relationship-entity triple structure data by combining identified entities and entity relationships based on the entity relationship group;
32) and converting unstructured triple structure data into structured data based on a data structure model, designing related algorithm logic, and completing technical layer construction of a system map.
4. A system for constructing a knowledge graph of manufacturing information, comprising:
the preprocessing module is used for understanding the initial system file through natural language, extracting entities according to a preset rule and arranging and forming triple information according to the relationship between the entities;
the application service module is used for providing a function query interface, realizing information interaction with the data layer and the front-end page through the interface, receiving data transmitted by the preprocessing module, and inputting the fused information into the graph database to form a knowledge graph of system information;
the data layer adopts a relational database and a graph database to store the text information, the entity basic information and the relationship between the entities,
the front-end page is used for realizing image drawing and UI display, converting user input into a request and sending the request to the back-end server;
and the back-end server realizes data interaction with the data layer and responds to the request sent by the front-end page.
5. The system for institutional information knowledgegraph construction according to claim 4, wherein said front end page employs a VUE framework with ElementUI, Axios and d3.js components.
6. The system for building institutional information knowledge graph according to claim 5, wherein the graph database of the data layer adopts a Neo4j database, and the relational database adopts an Oracle database.
7. The system for institutional information knowledge graph construction according to claim 6 wherein said back end server employs a Springboot framework.
8. The system information knowledge graph construction system according to claim 7, wherein a user inputs query conditions, Element-UI triggers related events according to user input, a request is sent to a back-end server through Axios, entity relationship data are updated to a D3.js drawing graph after query results are obtained from a relational database, entity detail data are updated to the Element-UI to show the query results, the back-end server realizes entity relationship data interaction with a Neo4j database, the back-end server realizes entity detail data interaction with an Oracle database, and the system information knowledge graph construction system responds to the request of Axios.
9. The system for institutional information knowledge graph building of claim 8, wherein said back-end server implements entity relationship data interaction with Neo4j database through API interface.
10. The system for institutional information knowledge graph building of claim 8 wherein said back end server implements entity detail data interaction with an Oracle database through an API interface.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150095303A1 (en) * | 2013-09-27 | 2015-04-02 | Futurewei Technologies, Inc. | Knowledge Graph Generator Enabled by Diagonal Search |
| CN110334212A (en) * | 2019-07-01 | 2019-10-15 | 南京审计大学 | A kind of territoriality audit knowledge mapping construction method based on machine learning |
| CN110597999A (en) * | 2019-08-01 | 2019-12-20 | 湖北工业大学 | Judicial case knowledge graph construction method of dependency syntactic analysis relation extraction model |
| CN112241401A (en) * | 2020-10-16 | 2021-01-19 | 中国民用航空华东地区空中交通管理局 | Knowledge graph-based digital quality management system and method |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150095303A1 (en) * | 2013-09-27 | 2015-04-02 | Futurewei Technologies, Inc. | Knowledge Graph Generator Enabled by Diagonal Search |
| CN110334212A (en) * | 2019-07-01 | 2019-10-15 | 南京审计大学 | A kind of territoriality audit knowledge mapping construction method based on machine learning |
| CN110597999A (en) * | 2019-08-01 | 2019-12-20 | 湖北工业大学 | Judicial case knowledge graph construction method of dependency syntactic analysis relation extraction model |
| CN112241401A (en) * | 2020-10-16 | 2021-01-19 | 中国民用航空华东地区空中交通管理局 | Knowledge graph-based digital quality management system and method |
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Application publication date: 20210914 |