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http://dx.doi.org/10.9708/jksci.2011.16.4.159

Collaborative Filtering Design Using Genre Similarity and Preffered Genre  

Kim, Kyung-Rog (Dept. of IT Application Tech., Hoseo Graduate School of Venture)
Byeon, Jae-Hee (Dept. of IT Application Tech., Hoseo Graduate School of Venture)
Moon, Nam-Mee (Dept. of IT Application Tech., Hoseo Graduate School of Venture)
Publication Information
Journal of the Korea Society of Computer and Information / v.16, no.4, 2011 , pp. 159-168 More about this Journal
Abstract
As e-commerce and social media service evolves, studies on recommender systems advance, especially concerning the application of collective intelligence to personalized custom service. With the development of smartphones and mobile environment, studies on customized service are accelerated despite physical limitations of mobile devices. A typical example is combined with location-based services. In this study, we propose a recommender system using movie genre similarity and preferred genres. A profile of movie genre similarity is generated and designed to provide related service in mobile experimental environment before prototyping and testing with data from MovieLens.
Keywords
recommender system; collaborative filtering; clustering; multi-property; interactive service; smart phone; LBS;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
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