Knowledge graph management method and system based on semantic space mapping

Abstract

The invention belongs to the technical field of text semantic processing and semantic webs, and particularly relates to a knowledge graph management method and system based on semantic space mapping. The method comprises the steps of semantic vector construction, semantic space mapping and knowledge graph management, wherein the step of knowledge graph management comprises three sub-steps of semantic clustering, semantic duplication eliminating and semantic annotation. A text unit describing edge / nodal points of a knowledge graph is projected to a semantic space, and vector representation of the edge / nodal points on the semantic space is obtained by vector accumulation; on the basis, multiple management tasks of the knowledge graph are achieved. The system correspondingly comprises a semantic vector construction module, a semantic space mapping module and a knowledge graph management module. The defects that a conventional knowledge graph management method is sensitive to factors such as word deformation, synonym variation and grammatical form variation are overcome, the situation of difference of the number of words can be easily handled in a vector accumulation mode, and further knowledge graph management tasks such as semantic clustering, semantic duplication eliminating and semantic annotation are easily achieved.

Description

Technical field [0001] The present invention is a semantic processing and semantic network technology field, which involves a knowledge graph management method and system based on semantic space -based mapping. Background technique [0002] Building a knowledge map is a major project in the era of big data. It can associate the messy data and sort it into structured knowledge to users. This feature determines that it will have important applications in many fields.The search is based on keyword matching. When the knowledge map is established, after entering a certain keyword, you can return the attributes, categories, relationships with other entities, etc.Can provide users with the required information more accurately and perfectly.The knowledge map is a series of applied cornerstones such as semantic search, machine automatic question and answer, Internet advertising recommendation, and personalized electronic reading. Whether it can effectively manage the knowledge map will di...

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Problems solved by technology

[0003] However, what is finally extracted in the current knowledge graph construction is a deterministic relationship representation, and this deterministic description is not adaptable to word deformation, synonym change, grammatical form change, etc., such as two semantic Since similar edges are described by different words, they will be regarded as two completely different edges. This processing method is not only unreasonable, but also brings problems to the management of knowledge graphs such as edge / node clustering, edge / node clustering, and edge / node clustering. Node deduplication, edge / node labeling, etc. bring huge difficulties, which affect the effective application of knowledge graphs

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