计算机应用研究2016，Vol.33Issue(10)：2988-2991,4.DOI:10.3969/j.issn.1001-3695.2016.10.027
一种结合用户可信度与相似度的鲁棒性推荐算法
Robust recommender algorithm based on user reliability and improved user similarity
摘要
Abstract
Shilling attacks pose a significant threat to the security of collaborative filtering recommender systems.It has come to be an important task to develop the attack-resistant techniques for robust collaborative recommendation.However,traditio-nal collaborative filtering algorithms have weakness in the balance between stability and predictive accuracy.To address this problem,this paper proposed user reliability and improved the calculation of user similarity,and incorporated both user relia-bility and similarity into standard collaborative filtering framework.Experiments show that the proposed algorithm performs bet-ter than state-of-the-art recommender algorithms in stability and predictive accuracy.关键词
协同过滤/托攻击/用户可信度/相似度/鲁棒性算法Key words
collaborative filtering/shilling attack/user reliability/similarity/robust algorithm分类
信息技术与安全科学引用本文复制引用
潘骏驰,张兴明,汪欣..一种结合用户可信度与相似度的鲁棒性推荐算法[J].计算机应用研究,2016,33(10):2988-2991,4.基金项目
国家“863”计划资助项目 （）
