Knowledge graph intelligent question-answering method based on relationship prediction

Abstract

The invention relates to a knowledge graph intelligent question-answering method based on relation prediction, and belongs to the field of natural language processing. The method comprises the following steps: S1, inputting a problem Q, and preprocessing the problem; S2, identifying an entity equalization in the problem by utilizing an entity identification technology, and mapping the entity equalization to a corresponding entity eKGs in the KGs; S3, querying the category c of the entity eKGs in the KGs, replacing the entity equest in the problem Q with the category c, and marking the categoryc as Qc; S4, mapping a relationship r from the Qc; S5, in the KGs, if there is no relation between the entity eKGs and the relation r; S6, learning new vector representation of the center entity eKGs; S7, deducing a hidden relationship in the KGs based on the existing related triples; and S8, obtaining an answer A based on knowledge graph reasoning of entities and relationships. According to themethod, the corresponding relation between the question entity and the knowledge graph entity and the corresponding relation between the question natural language description and the knowledge graph semantic relation can be found.

Description

technical field [0001] The invention belongs to the field of natural language processing, and relates to a knowledge map intelligent question answering method based on relationship prediction. Background technique [0002] The keyword-based search method of traditional search engines lacks semantic analysis and semantic understanding of natural language, which has become increasingly difficult to meet people's needs. For users, the interaction mode that conforms to the expression of human natural language is the best. When the question answering system shows enough intelligence, it can meet the needs of users for this interaction mode. Google proposed the concept of Knowledge Graphs (KGs) in 2012 to further promote the question answering system in the direction of intelligence. With the development of knowledge graph technology, intelligent question answering system has shown new development prospects. The rise of social networking sites has provided a large amount of real...

AI Technical Summary

Problems solved by technology

[0002] The keyword-based search method of traditional search engines lacks semantic analysis and semantic understanding of natural language, which has become increasingly difficult to meet people's needs

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