Ranking web pages from user perspectives of social bookmarking sites

Chia Hao Lo*, Wen-Chih Peng, Meng Fen Chiang

*Corresponding author for this work

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

2 Scopus citations

Abstract

Recently, the growth of social bookmark sites (e.g., del.icio.us) brings a new way to organize and share web pages. Specially, the social bookmarking sites contain many bookmarks of users, and users, who bookmark web pages, would frequently browse these pages in the future. Therefore, we argue that social bookmarking sites provide the readers' perspective and are able to take the perspective into consideration in ranking web pages. In this paper, we propose two ranking algorithms, ExpertVoteRank and RecommendationPageRank, to reveal the diverse information of web pages in the social bookmarking sites. The concept of both algorithms are based on the views of readers: ExpertVoteRank takes advantage of experts of readers, while RecommendationPageRank applies recommendations from crowds to web pages. Note that we collected about 90 millions data. Experiments show that both algorithms have effectiveness to rank web pages according to the viewpoint of users.

Original languageEnglish
Title of host publicationProceedings - 2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008
Pages155-161
Number of pages7
DOIs
StatePublished - 1 Dec 2008
Event2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008 - Sydney, NSW, Australia
Duration: 9 Dec 200812 Dec 2008

Publication series

NameProceedings - 2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008

Conference

Conference2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008
CountryAustralia
CitySydney, NSW
Period9/12/0812/12/08

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