郑州大学学报（工学版）2012，Vol.33Issue(5)：118-120,3.DOI:10.3969/j.issn.1671-6833.2012.05.026
基于加权信息熵相似性的协同过滤算法
Collaborative Filtering Algorithm Based on Weighted Information Entropy Similarity
摘要
Abstract
Collaborative filtering algorithm is one of the most successful recommender system technology. The similarity calculation is the core of the collaborative filtering algorithm. In view of the poor predication quality existing in traditional similarity calculation with sparse data, we propose a similarity calculation method based on the information entropy between differences of items. First,we weight the entropy by the difference and common evaluation and then normalized it to measure the similarity between items. Verified by experiments with i-tem-based collaborative filtering algorithm, the results show that it improves accuracy of personalized recommendation.关键词
信息熵加权/相似度计算/协同过滤/个性化推荐Key words
weighted information entropy/ similarity calculation/ collaborative filtering/ personalized recommendation分类
信息技术与安全科学引用本文复制引用
刘文龙,张桂芸,陈喆,朱蔷蔷..基于加权信息熵相似性的协同过滤算法[J].郑州大学学报（工学版）,2012,33(5):118-120,3.基金项目
国家自然科学基金资助项目(60970060) （60970060）
天津市教委资助项目(20071328) （20071328）
天津市科技支撑计划重点项目(09ZCKFGX00500) （09ZCKFGX00500）
天津师大博士基金项目(52LX17) （52LX17）
