Information Filtering Using User‘s Context on Browsing in Hypertext
User Modeling and User-Adapted Interaction
Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Estimating the size and evolution of categorised topics in web directories
Web Intelligence and Agent Systems
Text mining in negative relevance feedback
Web Intelligence and Agent Systems
Web Intelligence and Agent Systems
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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.