Abstract
TFIDF was widely used in IR system based on the vector space model (VSM). Pagerank was used in systems based on hyperlink structure such as Google. It was necessary to develop a technique combining the advantages of two systems. In this paper, we drew up a framework by using the content of web pages and the out-link information synchronously. We set up a matrix M, which composed of out-link information and the relevant value of web pages with the given query. The relevant value was denoted by TFIDF. We got the NewPR (New Pagerank) by solving the equation with the coefficient M. Experimental results showed that more pages, which were more important both in content and hyper-link sides, were selected. © Springer-Verlag Berlin Heidelberg 2006.
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CITATION STYLE
Wang, H. M., Rajman, M., Guo, Y., & Feng, B. Q. (2006). New PR-combining TFIDF with pagerank. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4132 LNCS-II, pp. 932–942). Springer Verlag. https://doi.org/10.1007/11840930_97
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