全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

一种基于用户信任网络的推荐方法

DOI: 10.13190/j.jbupt.2014.04.021, PP. 98-102

Keywords: 社会网络,社会化推荐,信任,协同过滤

Full-Text   Cite this paper   Add to My Lib

Abstract:

为了解决推荐中存在的数据稀疏、准确度不高等问题,提出了一种基于用户信任网络的推荐方法.首先利用基本的社会网络,融合用户的基本信任关系、角色影响力、属性相似关系、偏好相似关系构造带权重的社会网络,然后基于此网络提出关键路径发现算法以发现满足约束条件的用户信任网络,最后基于用户信任网络进行推荐.在Filmtipset数据集上对影响推荐质量的各个因素进行了对比分析,结果表明,基于用户信任网络的方法能得到更好的推荐效果.

References

[1]  Deng Ailin, Zhu Yangyong, Shi Bole. A collaborative filtering recommendation algorithm based on item rating prediction[J]. Journal of Software, 2003, 14(9): 1621-1628. 邓爱林, 朱扬勇, 施伯乐. 基于项目评分预测的协同过滤推荐算法[J]. 软件学报, 2003, 14(9): 1621-1628.
[2]  Adomavicius G, Tuzhilin A. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions[J]. IEEE Transactions on Knowledge and Data Engineering, 2005, 17(6): 734-749.
[3]  Golbeck J, Hendler J. Inferring binary trust relationships in web-based social networks[J]. ACM Transactions on Internet Technology (TOIT), 2006, 6(4): 497-529.
[4]  Adamic L A, Lukose R M, Huberman B A. Local search in unstructured networks[J]. Handbook of Graphs and Networks, 2003: 295.
[5]  Liu Guanfeng, Wang Yan, Orgun M A, et al. A heuristic algorithm for trust-oriented service provider selection in complex social networks[C]//Proc of the 2010 IEEE International Conference on Services Computing (SCC). IEEE, 2010: 130-137
[6]  Liu Yingchun, Zheng Xiaolin, Chen Deren. Trust predicting using roles-based reputation in trust network[J]. Journal of Beijing University of Posts and Telecommunications, 2013, 36(1): 72-76. 刘迎春, 郑小林, 陈德人. 信任网络中基于角色信誉的信任预测[J]. 北京邮电大学学报, 2013, 36(1): 72-76.
[7]  Milgram S. The small world problem[J]. Psychology Today, 1967, 2(1): 60-67.
[8]  Said A, Berkovsky S, De L E W. Introduction to special section on CAMRA2010: movie recommendation in context[J]. ACM Transactions on Intelligent Systems and Technology(TIST), 2013, 4(1): 13.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133