作者
Blerina Lika, Kostas Kolomvatsos, Stathes Hadjiefthymiades
发表日期
2014/3/1
期刊
Expert systems with applications
卷号
41
期号
4
页码范围
2065-2073
出版商
Pergamon
简介
A recommender system (RS) aims to provide personalized recommendations to users for specific items (e.g., music, books). Popular techniques involve content-based (CB) models and collaborative filtering (CF) approaches. In this paper, we deal with a very important problem in RSs: The cold start problem. This problem is related to recommendations for novel users or new items. In case of new users, the system does not have information about their preferences in order to make recommendations. We propose a model where widely known classification algorithms in combination with similarity techniques and prediction mechanisms provide the necessary means for retrieving recommendations. The proposed approach incorporates classification methods in a pure CF system while the use of demographic data help for the identification of other users with similar behavior. Our experiments show the performance of …
学术搜索中的文章
B Lika, K Kolomvatsos, S Hadjiefthymiades - Expert systems with applications, 2014