自动化学报Issue(5)：1004-1012,9.DOI:10.16383/j.aas.2015.c140073
基于用户声誉的鲁棒协同推荐算法
Robust Collaborative Recommendation Algorithm Based on User0s Reputation
摘要
Abstract
With the rapid development of recommender systems in e-commerce industry, such systems bring huge eco-nomic profits. As a consequence, shilling attacks pose a significant threat to the security of collaborative filtering rec-ommender systems. Developing a kind of robust recommendation technology which can resist attacks has become an important issue in the field of the recommender system at present. In this paper, a reputation recommender system is built by user reputations which are obtained from the user historical records. Utilizing the latent factor model in the field of collaborative filtering recommendation, a novel robust collaborative recommendation algorithm based on user reputations is proposed. The algorithm improves the system0s robustness from two aspects of shilling attack and natural noise. Empirical results on Movielens 1M dataset demonstrate that compared with the existing robust recommendation, this algorithm is very effective. Characterized by simplicity, interpretability and stability, the algorithm has strong ability to resist the system attack along with the accuracy getting a certain improvement.关键词
推荐系统/协同过滤/声誉/托攻击Key words
Recommender system/collaborative filtering/reputation/shilling attack引用本文复制引用
张燕平,张顺,钱付兰,张以文..基于用户声誉的鲁棒协同推荐算法[J].自动化学报,2015,(5):1004-1012,9.基金项目
国家自然科学基金(61175046),安徽大学青年科学基金(KJQN1116),安徽省自然科学基金项目(1408085MF132),教育部人文社科青年基金(14YJC860020)资助Supported by National Natural Science Foundation of China (61175046), Youth Science Fund of Anhui Univer-sity (KJQN1116), Natural Science Found of Anhui Province (1408085MF132), and Humanities and Social Science Youth Fund of Ministry of Education (14YJC860020) （61175046）
