Personalized Query Expansion Model Based on Latent Semantic Analysis
Weimin Xu · Jisuanji gongcheng · 2010
In order to improve the quality of information retrieval systems,this paper proposes a complex and personalized model of query expansion. The proposed approach constructs a latent semantic space to get semantic concept related and interest related words. In this way,the model solves the famous vocabulary problem and meets various users' needs. Experiments show this algorithm can significantly improve precision,recall and efficiency in information retrieval,meeting different users' requirements in search engine systems.