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Discovering User Access Pattern Based on Probabilistic Latent Factor Model

9 years 3 months ago
Discovering User Access Pattern Based on Probabilistic Latent Factor Model
There has been an increased demand for characterizing user access patterns using web mining techniques since the informative knowledge extracted from web server log files can not only offer benefits for web site structure improvement but also for better understanding of user navigational behavior. In this paper, we present a web usage mining method, which utilize web user usage and page linkage information to capture user access pattern based on Probabilistic Latent Semantic Analysis (PLSA) model. A specific probabilistic model analysis algorithm, EM algorithm, is applied to the integrated usage data to infer the latent semantic factors as well as generate user session clusters for revealing user access patterns. Experiments have been conducted on real world data set to validate the effectiveness of the proposed approach. The results have shown that the presented method is capable of characterizing the latent semantic factors and generating user profile in terms of weighted page vecto...
Guandong Xu, Yanchun Zhang, Jiangang Ma, Xiaofang
Added 26 Jun 2010
Updated 26 Jun 2010
Type Conference
Year 2005
Where ADC
Authors Guandong Xu, Yanchun Zhang, Jiangang Ma, Xiaofang Zhou
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