Knowledge graph generation method based on multiple indexes

Abstract

The invention discloses a knowledge graph generation method based on multiple indexes, and belongs to the technical field of computer text processing, and the generation method comprises the following specific steps: (1) information extraction; (2) knowledge fusion; (3) knowledge processing; (4) knowledge updating; according to the invention, tourism websites and Baidu encyclopedia are taken as data sources, entities are extracted by taking word segmentation, word removal and part-of-speech tagging as extraction modes, and meanwhile, entity relationships and entity attributes are extracted based on expert definition rules, so that the data extraction is relatively accurate, and the follow-up tourism field atlas application search accuracy can be improved; besides, the confidence degree is used as a judgment basis, the confidence degree is composed of a word vector, a sentence vector and an editing distance, and the tourism field knowledge graph is subjected to long-term incremental updating through the confidence degree, so that the quality of the tourism field knowledge graph is guaranteed for a long time, and the accurate searching capability of the tourism domain knowledge graph is continuously improved.

Description

technical field [0001] The invention relates to the technical field of computer text processing, in particular to a multi-indicator-based knowledge map generation method. Background technique [0002] After retrieval, Chinese Patent No. CN110347843A discloses a method for building a knowledge service platform in the field of Chinese tourism based on knowledge graphs. Although this inventive method can provide one-stop comprehensive services, it cannot perform long-term high-quality updates, which is not conducive to application In the ever-changing field of tourism; Knowledge Graph, known as knowledge domain visualization or knowledge domain mapping map in the library and information industry, is a series of different graphics showing the knowledge development process and structural relationship, described by visualization technology Knowledge resources and their carriers, excavating, analyzing, constructing, drawing and displaying knowledge and their interrelationships; cur...

AI Technical Summary

Problems solved by technology

[0002] After retrieval, Chinese Patent No. CN110347843A discloses a method for building a knowledge service platform in the field of Chinese tourism based on knowledge graphs. Although this inventive method can provide one-stop comprehensive services, it cannot perform long-term high-quality updates, which is not conducive to application In the ever-changing field of tourism; Knowledge Graph, known as knowledge domain visualization or knowledge domain mapping map in the library and information industry, is a series of different graphics showing the knowledge development process and structural relationship, described by visualization technology Knowledge resources and their carriers, excavating, analyzing, constructing, drawing and displaying knowledge and their interrelationships; currently, with the rapid development of Internet technology and tourism, users can use computers or smart phones and other devices to conveniently browse on the Internet However, it still takes a lot of time and energy for users to inquire about travel knowledge. How to make full use of a large amount of relevant data in the Internet to automatically provide users with accurate travel knowledge services is an important issue in the current tourism field. An urgent problem to be solved; therefore, it is particularly important to invent a multi-indicator-based knowledge map generation method;

[0003] At present, compared with general knowledge graphs, there are relatively few construction and researches on tourism knowledge graphs, and there are many problems in the existing tourism knowledge graphs. The data sources and data extraction are not accurate enough, resulting in relatively low search accuracy in tourism graphs. Poor, and this kind of tourism map does not have the ability to automatically update. For the multi-variant tourism field, the application scenarios and time of this kind of tourism map are very limited. Therefore, we propose a multi-indicator-based knowledge Atlas generation method

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