DocumentCode :
3558795
Title :
Providing Justifications in Recommender Systems
Author :
Symeonidis, Panagiotis ; Nanopoulos, Alexandros ; Manolopoulos, Yannis
Author_Institution :
Dept. of Inf., Aristotle Univ., Thessaloniki
Volume :
38
Issue :
6
fYear :
2008
Firstpage :
1262
Lastpage :
1272
Abstract :
Recommender systems are gaining widespread acceptance in e-commerce applications to confront the ldquoinformation overloadrdquo problem. Providing justification to a recommendation gives credibility to a recommender system. Some recommender systems (Amazon.com, etc.) try to explain their recommendations, in an effort to regain customer acceptance and trust. However, their explanations are not sufficient, because they are based solely on rating or navigational data, ignoring the content data. Several systems have proposed the combination of content data with rating data to provide more accurate recommendations, but they cannot provide qualitative justifications. In this paper, we propose a novel approach that attains both accurate and justifiable recommendations. We construct a feature profile for the users to reveal their favorite features. Moreover, we group users into biclusters (i.e., groups of users which exhibit highly correlated ratings on groups of items) to exploit partial matching between the preferences of the target user and each group of users. We have evaluated the quality of our justifications with an objective metric in two real data sets (Reuters and MovieLens), showing the superiority of the proposed method over existing approaches.
Keywords :
electronic commerce; information filtering; information filters; content data; customer acceptance; customer trust; e-commerce application; information overload problem; partial matching; rating data; recommender system credibility; target user preference; user feature profile; Collaborative filtering (CF); content-based filtering (CB); e-commerce; justification; recommender systems;
fLanguage :
English
Journal_Title :
Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on
Publisher :
ieee
ISSN :
1083-4427
Type :
jour
DOI :
10.1109/TSMCA.2008.2003969
Filename :
4648950
Link To Document :
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