The Community for Technology Leaders
RSS Icon
Issue No.11 - November (2011 vol.23)
pp: 1691-1703
Laurence A.F. Park , University of Western Sydney, Penrith South DC
Kotagiri Ramamohanarao , The University of Melbourne, Melbourne
Web link analysis methods such as PageRank, HITS, and SALSA have focused on obtaining global popularity or authority of the set of Web pages in question. Although global popularity is useful for general queries, we find that global popularity is not as useful for queries in which the global population has less knowledge of. By examining the many different communities that appear within a Web page graph, we are able to compute the popularity or authority from a specific community. Multiresolution popularity lists allow us to observe the popularity of Web pages with respect to communities at different resolutions within the Web. Multiresolution popularity lists have been shown to have high potential when compared against PageRank. In this paper, we generalize the multiresolution popularity analysis to use any form of Web page link relations. We provide results for both the PageRank relations and the In-degree relations. By utilizing the multiresolution popularity lists, we achieve a 13 percent and 25 percent improvement in mean average precision over In-degree and PageRank, respectively.
Symmetric nonnegative matrix factorization, PageRank, SALSA, in-degree, Web link analysis.
Laurence A.F. Park, Kotagiri Ramamohanarao, "Multiresolution Web Link Analysis Using Generalized Link Relations", IEEE Transactions on Knowledge & Data Engineering, vol.23, no. 11, pp. 1691-1703, November 2011, doi:10.1109/TKDE.2011.107
[1] L. Page, S. Brin, R. Motwani, and T. Winograd, "The Pagerank Citation Ranking: Bringing Order to the Web," technical report, Stanford Digital Library Technologies Project, psu.edupage98pagerank.html , 1998.
[2] J.M. Kleinberg, "Authoritative Sources in a Hyperlinked Environment," J. ACM, vol. 46, no. 5, pp. 604-632, 1999.
[3] R. Lempel and S. Moran, "SALSA: The Stochastic Approach for Link-Structure Analysis," ACM Trans. Information Systems, vol. 19, no. 2, pp. 131-160, Apr. 2001.
[4] L.A.F. Park and K. Ramamohanarao, "Mining Web Multi-Resolution Community-Based Popularity for Information Retrieval," Proc. ACM Conf. Information and Knowledge Management, pp. 545-552, Nov. 2007.
[5] M. Najork, "Comparing the Effectiveness of HITS and SALSA," Proc. ACM 16th Conf. Information and Knowledge Management, M.J. Silva, A.A.F. Laender, R. Baeza-Yates, D.L. McGuinness, B. Olstad, Ø.H. Olsen, and A.O. Falcão, eds., pp. 157-164, 2007.
[6] C. Ding, X. He, and H.D. Simon, "On the Equivalence of Nonnegative Matrix Factorization and Spectral Clustering," Proc. SIAM Int'l Conf. Data Mining (SDM '05), pp. 606-610, Apr. 2005.
[7] I. Soboroff, "Does WT10g Look Like the Web?" SIGIR '02: Proc. 25th Ann. Int'l ACM SIGIR Conf. Research and Development in Information Retrieval, pp. 423-424, 2002.
[8] Y. Zhang, L.A.F. Park, and A. Moffat, "Click-Based Evidence for Decaying Weight Distributions in Search Effectiveness Metrics," Information Retrieval, vol. 13, pp. 1-24, 2010.
[9] T.H. Haveliwala, "Topic-Sensitive Pagerank," WWW '02: Proc. 11th Int'l Conf. World Wide Web, pp. 517-526, 2002.
[10] G. Jeh and J. Widom, "Scaling Personalized Web Search," WWW '03: Proc. 12th Int'l Conf. World Wide Web, pp. 271-279, 2003.
[11] T.G. Kolda, B.W. Bader, and J.P. Kenny, "Higher-Order Web Link Analysis Using Multilinear Algebra," Proc. Fifth IEEE Int'l Conf. Data Mining, pp. 242-249, 2005.
24 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool