A Fuzzy MCDM Based Approach for Hybrid Recommender Systems

作     者：Yi Peng,Wenli Zhang,and Gang Kou School of Management and Economics,University of Electronic Science and Technology of China,Chengdu 610054,PR China Yong Shi College of Information Science & Technology,University of Nebraska at Omaha,Omaha,NE 68182,USA and Research Center on Fictitious Economy and Data Sciences,Chinese Academy of Sciences,Beijing 100190,China 

会议名称：《第六届（2011）中国管理学年会——商务智能分会场》

会议日期：2011年

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by grants from the National Natural Science Foundation of China (#70901011,#70901015,and # 70921061) the Fundamental Research Funds for the Central Universities 

摘      要：Recommender systems are the most widely used techniques to overcome information ***,most of current techniques make recommendations based on single *** this study,we propose a new hybrid recommendation approach based on Fuzzy Multiple Criteria Decision Making （MCDM） *** MCDM methods,DEMATEL and TOPSIS are integrated with traditional collaborative filtering and content-based *** order to evaluate proposed approach,we collect data from survey questionnaire with users from ***,the largest Chinese website devoted for movies,books,and music *** use oversampling technique to simulate the recommendation data set in multi-criteria *** result shows that proposed approach can improve the hit rate comparing to collaborative filtering recommendation.