A Report of Activities at the WIC-India Research Center
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
A Web Surfer Model Incorporating Topic Continuity
IEEE Transactions on Knowledge and Data Engineering
Fuzzy web surfer models: theory and experiments
WImBI'06 Proceedings of the 1st WICI international conference on Web intelligence meets brain informatics
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PageRank is primarily based on link structure analysis. Recently, it has been shown that content information can be utilized to improve link analysis. We propose a novel algorithm that harnesses the information contained in the history of a surfer to determine his topic of interest when he is on a given page. As the history is unavailable until query time, we guess it probabilistically so that the operations can be performed of.ine. This leads to a better web page categorization and, thereby, to a better ranking of web pages.