An entity linking method based on graph model

Abstract

The invention discloses an entity linking method based on a graph model, which is mainly used for dealing with the entity linking problem of unstructured text. The method includes the steps of firstlyconstructing an entity association diagram of the same text by using all entity reference items obtained in the same text and the corresponding candidate entity set as the basis of the dynamic entitydisambiguation algorithm; then, through the dynamic entity disambiguation algorithm based on graph and PageRank, selecting the highest-scoring undisambiguated candidate entity as the target entity ofentity reference in each round, and completing the disambiguation selection process of entity reference corresponding to multiple candidate entities step by step; at last, utilizing XGBoost in a machine learning domain to judge the target entity, linking the logged-in target entity correctly, and identifying the unlogged target entity correctly.

Description

technical field

[0001] The invention belongs to the field of entity linking and relates to an entity linking method based on a graph model. Background technique

[0002] Since the concept of the Semantic Web was proposed, more and more open link data and user-generated content have been published on the Internet, and the Internet has gradually changed from a document that only contains hyperlinks between web pages to a World Wide Web that contains a large number of descriptions of various entities and A World Wide Web of Data rich in relationships between entities. While Internet webpages, such as news, blogs, etc., involve a large number of entities, most of the webpages themselves do not have relevant descriptions and background introductions about these entities. In order to help people better understand the content of the webpage, many websites or authors will establish a link relationship between the entities that appear in the webpage and the corresponding knowledge b...

Images