System and method for assisting in generating domain knowledge graph

Abstract

The invention discloses a system and method for assisting in generating a domain knowledge graph, and the system comprises a basic library module, a knowledge graph auxiliary construction module, a submitted data integration processing module and a knowledge graph output module, and the basic library module comprises a knowledge construction model library, a knowledge construction algorithm library, a domain knowledge library and a knowledge graph output symbol library. The knowledge construction model library, the knowledge construction algorithm library and the domain knowledge base are electrically connected with the knowledge graph auxiliary construction module; through cooperation of the basic library module, the knowledge graph auxiliary construction module, the submitted data integration processing module and the knowledge graph output module, the basic library module comprises a knowledge construction model library, a knowledge construction algorithm library, a domain knowledge library and a knowledge graph output symbol library, and knowledge expansion is performed by adopting a preset knowledge construction model. Therefore, the quality of the finally generated knowledge graph can be effectively ensured.

Description

technical field [0001] The invention belongs to the technical field of knowledge graphs, and in particular relates to a system and method for assisting the generation of domain knowledge graphs. Background technique [0002] Knowledge Graph (Knowledge Graph), also known as knowledge domain visualization or knowledge domain mapping map, is a series of different graphs showing the knowledge development process and structural relationship. Mapping and displaying knowledge and their interconnections. Knowledge graph is essentially a structured semantic knowledge base, which aims to describe various concepts and entities existing in the real world and their interrelationships, and can provide practical and valuable references for scientific research. [0003] In the prior art, knowledge maps are usually generated based on mind mapping and concept map technologies, or knowledge maps are constructed by extracting relevant knowledge from network resources such as encyclopedias; amo...

AI Technical Summary

Problems solved by technology

However, this approach faces two key difficulties

First of all, with Wikipedia and other network resources as data sources, the accuracy, scientificity, and integrity of knowledge cannot be guaranteed, especially in some cutting-edge fields.

Secondly, the knowledge extracted from data of different sources and different structures is often disorganized. It takes a large amount of complex information processing in the later stage, including manual classification, labeling and other cumbersome operations to finally build a relatively well-formed knowledge graph. Moreover, the quality also cannot be guaranteed

In addition, in the knowledge map constructed by the above method, data mapping of knowledge entities, relationships and attributes is often only used, such as lines, and the visualization performance is not strong.

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