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http://dx.doi.org/10.17662/ksdim.2019.15.3.129

A Situation-Based Recommendation System for Exploiting User's Mood  

Kim, Younghyun (한국소방산업기술원 기술연구소)
Lim, Woo Sub (한국소방산업기술원 기술연구소)
Jeong, Jae-Han (한국소방산업기술원 기술연구소)
Lee, Kyoung-Jun (경희대학교 경영대학)
Publication Information
Journal of Korea Society of Digital Industry and Information Management / v.15, no.3, 2019 , pp. 129-137 More about this Journal
Abstract
Recommendation systems help users by suggesting items such as products, services, and information. However, most research on recommendation systems has not considered people's moods although the appropriate contents recommended to people would be changed by people's moods. In this paper, we propose a situation-based recommendation system which exploits people's mood. The proposed scheme is based on the fact that the mood of a user is changed frequently by the surrounding environments such as time, weather, and anniversaries. The environments are defined as feature identifications, and the rating values on items are stored as feature identifications at a database. Then, people can be recommended diverse items according to their environments. Our proposed scheme has some advantages such as no problem of cold start, low processing overhead, and serendipitous recommendation. The proposed scheme can be also a good option as of assistance to other recommendation systems.
Keywords
Recommender System; Database; Mood; Serendipitous Recommendation;
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Times Cited By KSCI : 4  (Citation Analysis)
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