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Document
Exploiting Community Behavior for Enhanced Link Analysis and Web Search

Authors: Julia Luxenburger and Gerhard Weikum

Published in: Dagstuhl Seminar Proceedings, Volume 7071, Web Information Retrieval and Linear Algebra Algorithms (2007)


Abstract
Methods for Web link analysis and authority ranking such as PageRank are based on the assumption that a user endorses a Web page when creating a hyperlink to this page. There is a wealth of additional user-behavior information that could be considered for improving authority analysis, for example, the history of queries that a user community posed to a search engine over an extended time period, or observations about which query-result pages were clicked on and which ones were not clicked on after a user saw the summary snippets of the top-10 results. We study enhancements of link analysis methods by incorporating additional user assessments based on query logs and click streams, including negative feedback when a query-result page does not satisfy the user demand or is even perceived as spam. Our methods use various novel forms of Markov models whose states correspond to users and queries in addition to Web pages and whose links also reflect the relationships derived from query-result clicks, query refinements, and explicit ratings.

Cite as

Julia Luxenburger and Gerhard Weikum. Exploiting Community Behavior for Enhanced Link Analysis and Web Search. In Web Information Retrieval and Linear Algebra Algorithms. Dagstuhl Seminar Proceedings, Volume 7071, pp. 1-17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)


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@InProceedings{luxenburger_et_al:DagSemProc.07071.8,
  author =	{Luxenburger, Julia and Weikum, Gerhard},
  title =	{{Exploiting Community Behavior for Enhanced Link Analysis and Web Search}},
  booktitle =	{Web Information Retrieval and Linear Algebra Algorithms},
  pages =	{1--17},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{7071},
  editor =	{Andreas Frommer and Michael W. Mahoney and Daniel B. Szyld},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.07071.8},
  URN =		{urn:nbn:de:0030-drops-10660},
  doi =		{10.4230/DagSemProc.07071.8},
  annote =	{Keywords: Query logs, link analysis, Markov reward model}
}
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