A novel approach of web search based on community wisdom

Weiliang Zhao*, Vijay Varadharajan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

1 Citation (Scopus)
14 Downloads (Pure)

Abstract

In this paper, we propose a novel approach for Web search based on the statistical information of local setting data of web browsers in a community. The members of the community share their local setting data of browsers and this enables them to take advantage of the peer community members's opinions in their Web search. Then we develop a new scheme that combines PageRank's link-based ranking scores with our proposed community based popularity scores for web sites. This hybrid scheme provides a rank-ordering method for search query results that integrates the content consumers' opinions with the content producers' opinions in a balanced manner. The users' opinions of web sites provide a solid starting point of trust for combatting web spam and improving the quality of Web search.

Original languageEnglish
Title of host publicationProceedings - 3rd International Conference on Internet and Web Applications and Services, ICIW 2008
EditorsA. Mellouk, J. Bi, G. Ortiz, D. K. W. Chiu, M. Popescu
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages431-436
Number of pages6
ISBN (Print)9780769531632
DOIs
Publication statusPublished - 2008
Event3rd International Conference on Internet and Web Applications and Services, ICIW 2008 - Athens, Greece
Duration: 8 Jun 200813 Jun 2008

Other

Other3rd International Conference on Internet and Web Applications and Services, ICIW 2008
CountryGreece
CityAthens
Period8/06/0813/06/08

Bibliographical note

Copyright 2008 IEEE. Reprinted from The Third International Conference on Internet and Web Applications and Services : ICIW 2008 : proceedings : 8-13 June 2008, Athens, Greece. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Macquarie University’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

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