Web Intelligence, IEEE / WIC / ACM International Conference on (2003)
Oct. 13, 2003 to Oct. 17, 2003
B. L. Narayan , Indian Statistical Institute
C. A. Murthy , Indian Statistical Institute
Sankar K. Pal , Indian Statistical Institute
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.
S. K. Pal, B. L. Narayan and C. A. Murthy, "Topic Continuity for Web Document Categorization and Ranking," Proceedings IEEE/WIC International Conference on Web Intelligence (WI 2003)(WI), Halifax, NS, Canada, 2003, pp. 310.