Knowledge graph data processing method and device

Abstract

The embodiment of the invention provides a knowledge graph data processing method and device. The method comprises the steps of selecting a currently-processed target entity from other entities; obtaining a first feature vector of an initial entity and obtaining a second feature vector of the target entity; calculating a feature value corresponding to the target entity according to the first feature vector and the second feature vector; for the maximum feature value, adopting the first feature vector and the second feature vector corresponding to the maximum feature value for updating the initial entity and classification information and relation information of the other entities. According to the knowledge graph data processing method and device, the entities and relation information in a knowledge graph are converted into vectorization, prediction of the classification information and relation information of the entities is convenient, and more intelligent semantic analysis and processing are further performed, semantic analysis and processing are automated, construction is achieved not based on rules, the labor and maintenance cost is lowered, and the application range is wider.

Description

technical field [0001] The present invention relates to the technical field of data processing, in particular to a data processing method of a knowledge graph and a data processing device of a knowledge graph. Background technique [0002] Knowledge map is also called scientific knowledge map. In the library and information industry, it is called knowledge domain visualization or knowledge domain mapping map. It is a series of different graphics showing the knowledge development process and structural relationship. Carriers that mine, analyze, construct, map and display knowledge and their interconnections. [0003] Specifically, the knowledge map combines the theories and methods of applied mathematics, graphics, information visualization technology, information science and other disciplines with metrology citation analysis, co-occurrence analysis and other methods, and uses a visual map to visually display the knowledge of the subject The core structure, development histo...

AI Technical Summary

Problems solved by technology

However, with the accumulation of knowledge, the data volume of the knowledge map increases and the structure becomes more and more complex. Accurate semantic analysis requires continuous addition and construction of query logic and rules

When the knowledge graph is constructed and the information is partially missing and the knowledge information is incomplete, it is very difficult and cumbersome to use rules to complete the knowledge graph

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