Aimed at the problem of theme drift of the entity context information

this paper proposes an entity disambiguation method based on biterm topic model. The proposed method considers that the entity has a different theme in a certain semantic environment and the other entity appearing in the same document at the same time can help the disambiguated entity to determine the referred content to a certain extent. Therefore

using the ideas of named entity constructing double words to incorporate collaborative entity relationship to the topic model

and on this basis

we conduct semi-supervised disambiguation using Wikipedia knowledge base. Finally

this paper conducts some relevant experiments on the web text data

and verifies the effectiveness of the proposed algorithm. The experiments show that the proposed method effectively improve the precision of entity disambiguation.