Ranking Web Pages from User Perspectives of Social Bookmarking Sites

• Published in: 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Vol. 1; pp. 155 - 161
• Main Authors: Lo, Chia-Hao, Peng, Wen-Chih, Chiang, Meng-Fen
• Format: Conference Proceeding
• Language: English
• Published: Washington, DC, USA IEEE Computer Society 09.12.2008; IEEE
• Series: ACM Conferences
• Subjects: Algorithm design and analysis; Bipartite graph; Computer science; Human-centered computing > Human computer interaction (HCI); Human-centered computing > Human computer interaction (HCI) > Interaction paradigms > Web-based interaction; Information systems > Information retrieval; Information systems > Information storage systems; Intelligent agent; Large-scale systems; Organizing; Ranking; social bookmarking sites and recommendation; Uniform resource locators; Voting; Web pages; Web search; social bookmarking sites and recommendation; Ranking
• ISBN: 9780769534961; 0769534961
• DOI: 10.1109/WIIAT.2008.350

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.