Using Wikipedia's Content for Cross-Website Page Recommendations that Consider Serendipity

A majority of web personalization research concentrates on customizing a single website. On the contrary, recommending web pages across websites is the focus of this study. We emphasize that eliciting user interests among different topics within a domain is an important concern in cross-website page recommendations. Enhancing Wikipedia's categorization system through heuristic information extraction, we constructed a system to study the coverage of a user's interests in order to promote serendipity, new and interesting information, in recommendations. We compared our system's performance regarding topicality and serendipity with the classical vector space model and obtained a slightly superior result.