标题: | Combining Reputation and Content-Based Filtering for Blog Article Recommendation in Social Bookmarking Websites |
作者: | Peng, Chi-Chieh Liu, Duen-Ren 資訊管理與財務金融系 註:原資管所+財金所 Department of Information Management and Finance |
关键字: | Web2.0;blog;Social bookmarking;clustering;Recommender System;Reputation System;Content-based filtering |
公开日期: | 2010 |
摘要: | The new generation of web-based communities, Web2.0, represents an innovative spirit in sharing and managing contents. Social bookmarking is a portal for users to share, organize, search, and manage bookmarks of web resources. However, with the rapid growth of web documents that are produced every day, people are facing the problem of information overload. The Social bookmarking web site provides the push (user recommendation) counts of articles indicating the recommended popularity degrees of articles. In this paper, we propose to derive the popularity degree of an article by considering the reputation of users that push the article. Moreover, we propose a personalized blog article recommendation approach, which combines the reputation-based popularity with content based filtering, to recommend popular blog articles to users that satisfy their personal preferences. Our experimental results show that the proposed approach outperforms conventional approaches. |
URI: | http://hdl.handle.net/11536/20768 |
ISBN: | 978-1-4503-1427-5 |
期刊: | PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON ELECTRONIC COMMERCE: ROADMAP FOR THE FUTURE OF ELECTRONIC BUSINESS |
起始页: | 8 |
结束页: | 14 |
显示于类别: | Conferences Paper |