Computing personalized pageranks

Authors:
Franco Scarselli;Ah Chung Tsoi;Markus Hagenbuchner
Affiliations:
University of Siena, Siena, Italy;Australian Research Council, Camberra, Australia;University of Wollongong, Wollongong, Australia
Venue:
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Year:
2004

Citing 6
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Abstract

A recently published approach to adaptive page rank, using the solution of quadratic optimization methods with a set of simple constraints, is modified to permit classification of web pages according to their page contents, URLs. This modification allows the approach to be more adapted to the needs of focussed crawlers, or personalized search engines.