Integrating Web Usage and Content Mining for More Effective Personalization
Electronic Commerce and Web Technologies, (2000)Abstract
Recent proposals have suggested Web usage mining as an enabling mechanism to overcome the problems associated with more traditional
Web personalization techniques such as collaborative or contentbased filtering. These problems include lack of scalability,reliance on subjective user ratings or static profiles, and the inability to capture a richer set of semantic relationshipsamong objects (in content-based systems). Yet, usage-based personalization can be problematic when little usage data is availablepertaining to some objects or when the site content changes regularly. For more effective personalization, both usage andcontent attributes of a site must be integrated into a Web mining framework and used by the recommendation engine in a uniformmanner. In this paper we present such a framework, distinguishing between the offline tasks of data preparation and mining,and the online process of customizing Web pages based on a user’s active session. We describe effective techniques based onclustering to obtain a uniform representation for both site usage and site content profiles, and we show how these profilescan be used to perform real-time personalization.
Description
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