Context-sensitive filtering for the web

Abstract

This paper proposes a filtering method on Web browsing. Some papers have reported that a user's interests shift continuously during browsing. To facilitate the user's browsing, a filtering system must adapt to the user's shift of interests. On the assumption that the user's interests are reflected in browsing page content and order, we have proposed Context-Sensitive Filtering (CSF) for a hypertext CD-ROM encyclopedia. In the encyclopedia, the entire hypertext is controlled to have one topic per page. We confirmed effectiveness of CSF for the encyclopedia. However, effectiveness of CSF for the Web was not confirmed. We inferred that the reason of failure is the difference in page properties of the Web and the encyclopedia. This paper describes modeling and CSF improvements. Main improvements include dividing a Web page to approximate an encyclopedia page and augmenting model calculation with TF-IDF. We confirmed effectiveness of proposed CSF through comparing several filtering methods.