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Abstract: In the original PageRank algorithm for improving the ranking of search-query results, a single PageRank vector is computed, using the link structure of the Web, to capture the relative "importance" of Web pages, independent of any particular search query. To yield more accurate search results, we propose computing a set of PageRank vectors, biased using a set of representative topics, to capture more accurately the notion of importance with respect to a particular topic. By using these... (Update)
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BibTeX entry: (Update)
Taher H. Haveliwala. Topic-sensitive PageRank. In Proceedings of the Eleventh International World Wide Web Conference, Honolulu, Hawaii, May 2002. http://citeseer.ist.psu.edu/article/haveliwala02topicsensitive.html More
@misc{ haveliwala02topicsensitive,
author = "T. Haveliwala",
title = "Topic-sensitive PageRank",
text = "Taher H. Haveliwala. Topic-sensitive PageRank. In Proceedings of the Eleventh
International World Wide Web Conference, Honolulu, Hawaii, May 2002.",
year = "2002",
url = "citeseer.ist.psu.edu/article/haveliwala02topicsensitive.html" }
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