Effective web personalization system based on time and semantic relatedness

The key aspect in building a Web personalization system is the user's navigational pattern. However, the navigational pattern alone is insufficient to capture the user's interest and behavior. This paper proposes a novel web personalization system that accepts the timing information, semantic information along with the navigational pattern, and classifies the users according their interest and behavior on the site. The proposed model is validated by constructing a Web personalization model using the real and synthetic data and the results are promising.