Combining Web Usage Mining and Fuzzy Inference for Website Personalization
Olfa Nasraoui · 2003
Personalization tailors a user’s interaction with the Web information space based on information gathered about them. Declarative user information such as manually entered profiles continue to raise privacy concerns and are neither scalable nor flexible in the face of very active dynamic Web sites and changing user trends and interests. One way to deal with this problem is through a complete automated Web personalization system. Such a system can be based on Web usage mining to discover Web usage profiles, followed by a recommendation system that can respond to the users’ individual interests. Significant amounts of error and uncertainty can permeate all the stages of Web personalization. Therefore, we present a fast and intuitive approach to provide Web recommendations using a fuzzy