Fuzzy Collaborative Filtering for Web Page Prediction

Web page prediction is a popular personalized service on the Web and has attracted much research attention. One of the most successful and widely used approaches is collaborative filtering. Traditional collaborative filtering requires explicit user participation for providing his/her interest to the pages. However, they suffer from some limitations such as additional user effort, user behavior alteration and data sparsity. A possible alternative is to use an implicit indicator which measures the time a user spends on a page. In this paper, we propose a new collaborative filtering algorithm based on the fuzzy set theory, which is designed to better address the sharp boundary problem of discretizing the viewing time. The experimental results show that the proposed methods can achieve a better performance than the Traditional CF without time information.