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Personalized Recommendation System using Level of Cosine Similarity of Emotion Word from Social Network  

Kwon, Eungju (Computer Science and Information Engineering, Inha University)
Kim, Jongwoo (Computer Science and Information Engineering, Inha University)
Heo, Nojeong (Information and Communication Technology, Dongyang University)
Kang, Sanggil (Computer Science and Information Engineering, Inha University)
Publication Information
Journal of Information Technology and Architecture / v.9, no.3, 2012 , pp. 333-344 More about this Journal
Abstract
This paper proposes a system which recommends movies using information from social network services containing personal interest and taste. Method for establishing data is as follows. The system gathers movies' information from web sites and user's information from social network services such as Facebook and twitter. The data from social network services is categorized into six steps of emotion level for more accurate processing following users' emotional states. Gathered data will be established into vector space model which is ideal for analyzing and deducing the information with the system which is suggested in this paper. The existing similarity measurement method for movie recommendation is presentation of vector information about emotion level and similarity measuring method on the coordinates using Cosine measure. The deducing method suggested in this paper is two-phase arithmetic operation as follows. First, using general cosine measurement, the system establishes movies list. Second, using similarity measurement, system decides recommendable movie list by vector operation from the coordinates. After Comparative Experimental Study on the previous recommendation systems and new one, it turned out the new system from this study is more helpful than existing systems.
Keywords
Movie Recommendation; Vector Space Model; Cosine Measure; Induction Measurement of Emotion Level;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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