Paper Info
Title
Ranking Web Pages from User Perspectives of Social Bookmarking Sites
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.
Year
DOI
Venue
2008
10.1109/WIIAT.2008.350
Web Intelligence
Keywords
Field
DocType
bookmark web page,social bookmarking site,social bookmarking sites,social bookmark site,ranking web page,information retrieval,expertvoterank,ranking web pages,recommendationpagerank,web page ranking,internet,user perspective,social bookmarking sites and recommendation.,share web page,ranking algorithm,ranking,social networking (online),diverse information,user perspectives,search engines,web page,millions data,web pages,association rules,bipartite graph
Data mining,Learning to rank,World Wide Web,Web page,Social media optimization,Information retrieval,Ranking,Computer science,Association rule learning,Web 2.0,Bookmarking,The Internet
Conference
Volume
ISBN
Citations 
1
978-0-7695-3496-1
1
PageRank 
References 
Authors
0.35
11
3
Name
Order
Citations
PageRank
Chia-Hao Lo1432.80
Wen-Chih Peng21645106.49
Meng-Fen Chiang3918.54