期刊文献+

社会化推荐研究进展 被引量:2

Research of Progress on Social Recommendation
下载PDF
导出
摘要 文章提供了一个关于社会化推荐研究进展的概述。随着推荐系统研究的不断深入,将社会化影响融入推荐系统成为一个新的研究热点和问题丰富的研究领域。首先描述了社会化推荐的相关技术:推荐系统和社会化网络分析。对当前社会化推荐的一些最新技术方法进行分类介绍,具体包括利用社会化关系推荐物品,利用社会化关系推荐好友,根据内容推荐社会化关系,小组推荐和为团体推荐五个方面。 This paper studies research progress on social recommendation.As the research of recommender system evolves,recommendation with social influence becomes a new hot topic and a problem-rich research area.This paper firstly describe the associated technologies,recommender systems and social network analysis.current technologies and approaches are classified for social recommendation,which includes item recommendation based on social network,person recommendation based on social network,person recommendation based on similar interest,team recommendation and recommendation for groups.
出处 《计算机与数字工程》 2012年第11期1-5,共5页 Computer & Digital Engineering
基金 国家自然科学基金(编号:11171148 61003024) 教育部人文社科基金(编号:10YJC870020 10YJC630283)资助
关键词 推荐系统 社会化推荐 社会化网络分析 recommender system social recommendation SNA
  • 相关文献

参考文献57

  • 1E. Rich,User Modeling via Stereotypes[J]. Cognitive Science, 1979,3 (4) : 329-354.
  • 2M. Powelh Approximation Theory and Methods [M]. Cam- bridge Univ. Press, 1981.
  • 3G. Salton. Automatic Text Proeessing[M]. Addison-Wesley, 1989.
  • 4M. Balabanovic and Y. Shoham, Fab: Content-Based, Collabora- tive Recommendation, Comm[J]. ACM, 1997,40 (3) : 66-72.
  • 5A. I. Schein, A. Popescul, L. H. Ungar, and D. M. Pennock. Methods and Metrics for Cold-Start Recommendations[C]// Proc. of the 25th Ann. Int'l ACM SIGIR Conf. ,2002.
  • 6H. Kautz,B. Selman, and M. Shah. Combining Social Networks and Collaborative Filtering[J]. Comm. ACM, 1997.
  • 7R. Sinha and K. Swearingen. Comparing recommendations made by online systems and friends[C]//Proc, of the DELOS Work- shop: Personalisation and Recommender Systems in Digital Li- braries, 2001.
  • 8H. Ma, I. King, and M. R. Lyu. Effective missing data prediction for collaborative filtering[C]//Proc, of the 30th Annual Inter- national ACM SIGIR Conference on Research and Development in Information Retrieval, 2007 : 39-46.
  • 9J. S. Breese, D. Heckerman, and C. Kadie. Empirical analysis of predictive algorithms for collaborative filtering [C]//Proc. of the 14th Conference on Uncertainty in Artificial Intelligence, 1998:43-52.
  • 10B. Sarwar, G. Karypis, J. Konstan, and J. Riedl. Item-Based collaborative filtering recommendation algorithms[C]//Proc. of the 10th International Conference on World Wide Web, 2001:285-295.

同被引文献15

引证文献2

二级引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部