Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Agents that reduce work and information overload
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Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Pattern matching algorithms
ParaSite: mining structural information on the Web
Selected papers from the sixth international conference on World Wide Web
Let's browse: a collaborative Web browsing agent
IUI '99 Proceedings of the 4th international conference on Intelligent user interfaces
Matching Hierarchical Structures Using Association Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
A fast string searching algorithm
Communications of the ACM
Modern Information Retrieval
Expert Systems: Principles and Programming
Expert Systems: Principles and Programming
IEEE Internet Computing
A System for Approximate Tree Matching
IEEE Transactions on Knowledge and Data Engineering
Learning from Hotlists and Coldlists: Towards a WWW Information Filtering and Seeking Agent
TAI '95 Proceedings of the Seventh International Conference on Tools with Artificial Intelligence
A machine learning approach to building domain-specific search engines
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Collaborative junk e-mail filtering based on multi-agent systems
HSI'03 Proceedings of the 2nd international conference on Human.society@internet
Extracting user interests from bookmarks on the web
PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining
CARSA – an architecture for the development of context adaptive retrieval systems
AMR'05 Proceedings of the Third international conference on Adaptive Multimedia Retrieval: user, context, and feedback
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A bookmark means the URL information stored for memorizing a user's own footprints and revisiting that website. This paper regards this bookmark as one of the most meaningful information representing user preferences. An original bookmark indicating only address information is categorized for merging semantic meanings by using public web directory services. These categorized bookmarks are expressed in a hierarchical tree structure. However, most current web directory services cannot afford to normalize and manage the topic hierarchy. There are several kinds of structural incompleteness such as multiple references and heterogeneous tree structures. In order to extract user prefer-ences, this paper proposes a method for driving these problems and the influence propagation methods based on Bayesian networks. Therefore, the preference maps representing users' interests are also established as tree structures. With respect to the user clustering, an approximate tree matching method is used for mapping (overlapping) users' preference maps. It is possible to make queries and process them efficiently according to categories. Finally, this paper is applied to implement collaborative web browsing that can guide and explore the web efficiently and adaptively.