软件导刊2016，Vol.15Issue(3)：52-56,5.DOI:10.11907/rjdk.1511423
一种个性化协同过滤混合推荐算法
A Kind of Personalized Collaborative Filtering Hybrid Recommendation Algorithm
摘要
Abstract
T raditional collaborative filtering algorithm exists poor recommendation quality for recommending to the user based solely on sparse rating matrix .A new comprehensive item similarity measurement algorithm based on information entropy is proposed in this paper to dispose the data sparse problem .Meanwhile ,taking into account the user's interest will change over time ,and the change is not same in different user groups ,this paper put forward the weight of adapt to different user interest changes ,which is inspired by Ebbinghaus's memory rule .The performed experiment based on the dataset of movielens shows that the modified algorithm can not only alleviate the problem of rating data sparse ,but also can improve the accuracy of the algorithm .关键词
推荐系统/协同过滤/项目属性/信息熵Key words
Recommend System/Collaborative Filtering/Item Attribute/Interest Change/Information Entropy分类
信息技术与安全科学引用本文复制引用
蒋宗礼,汪瑜彬..一种个性化协同过滤混合推荐算法[J].软件导刊,2016,15(3):52-56,5.基金项目
北京市重点学科基金项目 （）
