Knowledge map representation learning method which combines entity and relationship description

Abstract

The invention discloses a knowledge map representation learning method which combines an entity and a relationship description. Text description information of the entity and the relationship is takeninto consideration, two information sources of structured information and the text description information of a triple are well integrated, based on combined extracts of an end-to-end model of neuralnetworks conducted on the entity and the relationship, a balance factor is set to balance the structured information and the text description information, and different score functions are defined according to different prediction objects; a loss function is used for correlating an entity vector and a relationship vector, the loss function is optimized, and when an optimization goal is reached, the vectors of each entity and relationship in the knowledge map and the text description information can be learned. The method solves the sparsity and imbalance of entity and relationship in a knowledge base, accurately and effectively represents the interconnection between the entity and relationship, applies the interconnection to the large-scale knowledge map, and has good practicality.

Description

Technical field [0001] The present invention relates to the field of knowledge graphs and deep learning technology, in particular to a knowledge graph representation learning method that integrates entity and relationship descriptions. Background technique [0002] With the advancement of technology and the times, today's society is developing at an astonishing speed, and we are gradually entering an era of intelligence and information. Massive new data and diverse information appear in different forms every day. The Internet has become the most effective and convenient information acquisition platform in today's society. With the increasing demand of Internet users for real information acquisition, how to obtain more accurate and effective information from massive data has become the focus of attention in many fields, and the knowledge graph has also become the focus of attention in many fields. produce. [0003] Google introduced knowledge graphs into search engines in May 2012...

AI Technical Summary

Problems solved by technology

[0005] What the present invention aims to solve is the problem that the existing knowledge map representation learning methods cannot effectively combine the text description information of entities and relations with structured information, and provides a knowledge map representation learning method that integrates entity and relation descriptions

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