RT - Journal Article T1 - Addressing the New User Cold-Start Problem in Recommender Systems Using Ordered Weighted Averaging Operator JF - ITRC YR - 2010 JO - ITRC VO - 2 IS - 4 UR - http://ijict.itrc.ac.ir/article-1-251-en.html SP - 79 EP - 87 K1 - OWA K1 - hybrid approach K1 - demographic- information K1 - content-based filtering K1 - collaborative filtering K1 - recommender system AB - Recommender systems have become significant tools in electronic commerce, proposing effectively those items that best meet the preferences of users. A variety of techniques have been proposed for the recommender systems such as, collaborative filtering and content-based filtering. This study proposes a new hybrid recommender system that focuses on improving the performance under the "new user cold-start" condition where existence of users with no ratings or with only a small number of ratings is probable. In this method, the optimistic exponential type of ordered weighted averaging (OWA) operator is applied to fuse the output of five recommender system strategies. Experiments using MovieLens dataset show the superiority of the proposed hybrid approach in the cold-start conditions. LA eng UL http://ijict.itrc.ac.ir/article-1-251-en.html M3 ER -