时间衰减制导的协同过滤相似性计算  

Time Decay Guided Similarity Calculation in Collaborative Filtering

作　　者：李源鑫[1] 肖如良[1] 陈洪涛[1] 赵婷[1] 李宏恩[1] 

机构地区：[1]福建师范大学软件学院,福州350108

出　　处：《计算机系统应用》2013年第11期129-134,158,共7页Computer Systems & Applications

基　　金：教育部规划基金(11YJA860028);福建省科技计划重大项目(2011H6006)

摘　　要：协同过滤算法中,相似性计算方法是整个推荐系统的关键,决定着推荐系统的推荐质量,为了提高相似性计算的精准性,提出了一种基于时间衰减的相似性计算方法.该方法在计算用户相似性时,考虑目标物品与共同评分物品的相似性,同时在计算用户与物品相似性时,考虑时间信息(用户对物品产生行为的时间)对相似性的影响.实验结果表明,该方法能够有效地避免传统相似性计算方法的不足,使推荐系统获得更好的推荐效果.In collaborative filtering algorithm, similarity calculation method is undoubtedly the key of the entn＇e recommender system, and determines the recommended quality of recommender system. In order to improve the precision of similarity calculation, a new similarity calculation method based on time decay is proposed. In this method, the similarity between the objective item and common-scored items is taken into account when calculating users similarity, and the influence of time information is taken into account when calculating users and items similarity. Experimental results shows that this method can effectively avoid the lack of the traditional similarity calculation method, and make the recommender system gain better recommendation result.

关 键 词：推荐系统 协同过滤 相似性计算 时间信息 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]