Abstract: Generation of integrated query interfaces is the important issue of Deep Web data integration．How to cluster different query interfaces effectively is one of the most core issues when generating integrated query interface．Due to the traditional vector space model can’t solve the shortage of relying on keyword maching in the Deep Web query interface clustering,the Latent Semantic Analysis (LSA) method was introduced and then the algorithm of Deep Web query interface clustering based on Latent Semantic Analysis was proposed．The experimental results on UIUC Web integration repository show that LSA method can significantly improve the performance of Deep Web query interface clustering.

Key words: Latent semantic analysis,Singular value decomposition,Deep Web,Query interface clustering