An optimization method of entity alignment based on graph partition

Abstract

The invention discloses an optimization method of entity alignment based on graph partition . Candidate entity pairs are mined from all entities by composite index, and whether the candidate entity pairs are aligned or not is judged by entity similarity measurement method, and then an optimization algorithm based on graph partition is proposed to improve the accuracy of equivalent entity alignmentby utilizing the similarity relationship between entities. The method of the invention solves the entity alignment problem of the large-scale Internet data, and can accurately and completely mine theentity set equivalent to each other in the original data.

Description

technical field [0001] The invention relates to an entity processing method in the database field, in particular to an entity alignment optimization method based on graph division. [0002] It involves inverted index and locality-sensitive hashing method in the field of database, TF-IDF model and Doc2Vec model in the field of machine learning, community partition algorithm in the field of social network, and entity alignment method in the field of semantic network. Background technique [0003] At present, Internet resources containing a large amount of information and knowledge have emerged on the Internet, such as Baidu Encyclopedia and Hudong Baike. There are natural data barriers between these different data sources, making it difficult to associate and interact with these data. However, if only a single data source is used to describe objects in the real world, there will be problems such as low object coverage and incomplete information description. Entity alignment ...

AI Technical Summary

Problems solved by technology

[0004] At present, there are three problems in the research of traditional entity alignment methods: (1) When only two data sources are used for entity matching, if all entity pairs are directly traversed, the computational complexity is proportional to the square of the data source size, and the computational cost is too high

On the Internet, entity data is generally represented in the form of a single page or document, and the current entity alignment method is not universal.

(3) In the case of multiple data sources, most of the current entity alignment methods transform it into the entity alignment problem of multiple pairs of data sources, without analyzing and calculating from the perspective of multiple data sources.

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