协同过滤推荐算法综述

Survey of Collaborative Filtering Algorithms

推荐系统是电子商务系统最重要的技术之一,协同过滤推荐是目前应用最广泛和最成功的推荐系统.介绍协同过滤推荐算法的基本思想和最新研究进展,分析目前出现的代表性算法.总结协同过滤推荐算法中的关键问题和相关解决方案,比如相似性比较,数据稀疏性问题,推荐的实时性,推荐策略,评估方法等,同时也对比分析各种方法的优缺点.最后介绍协同过滤推荐算法需要进一步解决的问题和可能的发展方向.

Recommender system in E-commerce analyzes preferences of users and presents recommendations, offering personalized purchase service. This paper presents an overview of the field of collaborative filtering recommender systems and describes main techniques applied in the current generation of collaborative filtering algorithm. This paper also describes various limitations of current recommendation methods and discusses the possible ways that can improve recommendation capabilities and make recommender systems applicable to an even larger range of applications.