Effective web content recommendation based on consumer behavior modeling

Web surfing has become an important activity for many consumers. We propose a web recommender that models user behavior by constructing a knowledge base using temporal web access patterns as input. We apply fuzzy logic to represent real-life temp oral concepts and requested resources of periodic pattern-based web access activities. The fuzzy representation is used to construct a knowledge base of the user's web access behaviors, which is then used to provide timely and personalized recommendations to the user, possibly on their portable devices. Experiments conducted to evaluate the performance of the proposed approach have shown very promising results. ©2011 IEEE.