Adaptive ranking of web pages

  • Authors:
  • Ah Chung Tsoi;Gianni Morini;Franco Scarselli;Markus Hagenbuchner;Marco Maggini

  • Affiliations:
  • University of Wollongong, Wollongong, Australia;Universita' degli studi di Siena, Siena, Italy;Universita' degli studi di Siena, Siena, Italy;University of Wollongong, Wollongong, Australia;Universita' degli studi di Siena, Siena, Italy

  • Venue:
  • WWW '03 Proceedings of the 12th international conference on World Wide Web
  • Year:
  • 2003

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Abstract

In this paper, we consider the possibility of altering the PageRank of web pages, from an administrator's point of view, through the modification of the PageRank equation. It is shown that this problem can be solved using the traditional quadratic programming techniques. In addition, it is shown that the number of parameters can be reduced by clustering web pages together through simple clustering techniques. This problem can be formulated and solved using quadratic programming techniques. It is demonstrated experimentally on a relatively large web data set, viz., the WT10G, that it is possible to modify the PageRanks of the web pages through the proposed method using a set of linear constraints. It is also shown that the PageRank of other pages may be affected; and that the quality of the result depends on the clustering technique used. It is shown that our results compared well with those obtained by a HITS based method.