A Web Recommendation Technique Based on Probabilistic Latent Semantic Analysis

Web transaction data between Web visitors and Web functionalities usually convey user task-oriented behavior pattern. Mining such type of clickstream data will lead to capture usage pattern information. Nowadays Web usage mining technique has become one of most widely used methods for Web recommendation, which customizes Web content to user-preferred style. Traditional techniques of Web usage mining, such as Web user session or Web page clustering, association rule and frequent navigational path mining can only discover usage pattern explicitly. They, however, cannot reveal the underlying navigational activities and identify the latent relationships that are associated with the patterns among Web users as well as Web pages. In this work, we propose a Web recommendation framework incorporating Web usage mining technique based on Probabilistic Latent Semantic Analysis (PLSA) model. The main advantages of this method are, not only to discover usage-based access pattern, but also to reveal...

• Type: Conference
• Year: 2005
• Where: WISE
• Authors: Guandong Xu, Yanchun Zhang, Xiaofang Zhou
• Keywords: Internet Technology, Usage Mining Technique, Usage Pattern, Web Usage Mining, WISE 2005