Method and device for combining entities in knowledge map

Abstract

The invention relates to a method and a device for combining entities in a knowledge map. The method comprises the following steps of generating a first-grade feature vector according to structural data corresponding to the entities in the knowledge map; generating a second-grade feature vector according to terms in documents corresponding to the entities; determining the similarity of the different entities according to the first-grade feature vector and the second-grade feature vector. According to the method and the device, the first-grade feature vector and the second-grade feature vector are constructed by entity IDs respectively, and the similarity of the entity IDs with the same name is calculated, and whether the entity IDs with the same name are the same object or not can be accurately judged, so that a condition that one object in the knowledge map has a plurality of entity IDs can be reduced, the content of the knowledge map is more accurate and the structure is more compact.

Description

technical field [0001] The invention relates to the technical field of computer search, in particular to a method and device for merging entities in a knowledge graph. Background technique [0002] Today, with the rapid development and popularization of computers, in order to obtain information and learn knowledge more conveniently and clearly, search engine services are more often used for information search and query. Because search engines obtain network resource information based on crawlers, and provide corresponding search results in the form of keyword matching, however, the search results are often varied, and sometimes cannot directly meet the specific precise or comprehensive needs of users. It may be necessary to adjust the search keywords to initiate multiple search requests, which is relatively inefficient and the user experience is poor. Therefore, further mining and more accurate classification of search resources are required. In addition, although the verti...

AI Technical Summary

Problems solved by technology

Because search engines obtain network resource information based on crawlers, and provide corresponding search results in the form of keyword matching, however, the search results are often varied, and sometimes cannot directly meet the specific precise or comprehensive needs of users. It may be necessary to adjust the search keywords to initiate multiple search requests, which is relatively inefficient and the user experience is poor. Therefore, further mining and more accurate classification of search resources are required.

In addition, although the vertical data that search engines can obtain from vertical websites is of high quality, errors and omissions sometimes occur, so it is necessary to deal with errors and supplement attributes

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