自动建立信任的防攻击推荐算法研究

 随着互联网中信息资源的日益增多,个性化推荐技术作为缓解"信息过载"的有效手段,得到了越来越多的研究者的关注.由于互联网天然的开放性,在商业利益的驱动下,部分恶意用户通过伪造虚假数据来影响系统的推荐结果,从而达到盈利的目的.本文提出一个自动建立信任的防攻击推荐算法,在考虑了用户评分相似性的基础上,引入适当的信任机制,通过为目标用户动态建立和维护有限数量的信任对象来获得可靠的推荐.大量基于真实数据集的实验表明,提出的算法能大大提高推荐系统的鲁棒性和可靠性,并在一定程度上提高了推荐的精准度.

Anti-Attack Recommender Algorithm Based on Automatic Trust Establishment

As the information resources available on the Internet are booming nowadays,personalized recommendation technique,which is an effective approach to ameliorate information overloading,has increasingly received attentions from researchers.Due to the native open nature of the Internet and driven by commercial motives,some malicious users attempt to influence the recommendation result via faking data,hoping to gain profits by manipulating recommendation.This paper proposes an anti-attack recommendation algorithm based on automatic trust establishment.Considering the similarities between user ratings,the proposed algorithm introduces a trust mechanism to obtain reliable recommendations through dynamically constructing and maintaining trusted references for users.Enormous experimental results obtained from real datasets reveal that the proposed algorithm could significantly improve both robustness and reliability of recommendation system,and meanwhile enhance the accuracy of recommendation to some extent.