Web clustering based on hybrid probabilistic latent semantic analysis model

Abstract

In E-commerce,in order to know more about the inherent characteristics of user access and make better marketing strategies,a Web clustering algorithm based on Hybrid Probabilistic Latent Semantic Analysis(H-PLSA) model was proposed in this paper.The Probabilistic Latent Semantic Analysis(PLSA) models were established respectively on user browsing data,page information and enhanced user transaction data by using PLSA technology.Using log-likelihood function,three PLSA models were merged to get the user clustering H-PLSA model and the page clustering H-PLSA model.Similarity calculation was based on the conditional probability among latent themes and user,page as well as site in the clustering analysis.The k-medoids algorithm based on distance was adopted in this clustering algorithm.The H-PLSA model was designed and constructed in this article,and the Web clustering algorithm was verified on this H-PLSA model.Then it is proved that the algorithm is effective.