Browse > Article
http://dx.doi.org/10.5392/JKCA.2016.16.12.181

Development of Personalized Media Contents Curation System based on Emotional Information  

Im, Ji-Hui (KT융합기술원)
Chang, Du-Seong (KT융합기술원)
Choe, Ho-Seop ((주)한국이디에스 융합서비스개발팀)
Ock, Cheol-Young (울산대학교 IT융합전공)
Publication Information
The Journal of the Korea Contents Association / v.16, no.12, 2016 , pp. 181-191 More about this Journal
Abstract
We analyzed the search word of the media content in the IPTV service, and as a result we found that an important factor is general meta information as well as content(material, plot, etc.) and emotion information in the media content selection criteria of customers. Therefore, in this research, in order to efficiently provide various media contents of IPTV to users, we designed the emotion classification system for utilizing the emotion information of the media content. Next, we proposed 'personalized media contents curation system based on emotion information' for organizing the media contents, through the various processing steps. Finally, to demonstrate the effectiveness of this system, we conducted a user satisfaction survey(72.0 points). In addition, the results of comparing the results based on popularity and the results of the proposed system showed that the ratio leading to the actual users' viewing behavior was 10 times higher.
Keywords
Emotion Curation; Emotion Classification; Personalized Recommendation; IPTV; Media Contents;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Carlos A. Gomez-Uribe and Neil Hunt, "The Netflix Recommender System: Algorithms, Business Value, and Innovation," Journal ACM Transactions on Management Information Systems (TMIS), Vol.6, No.13, 2016.
2 http://terms.naver.com/entry.nhn?docId=1691524&cid=42171&categoryId=42190
3 R. Burke, "Hybrid Recommender Systems: Survey and Experiments," User Modeling and User-Adapted Interaction, Vol.12, No.4, pp.331-370, 2002(11).   DOI
4 Francesco Ricci, Recommender Systems Handbook, Springer, 2011.
5 G. Adomavicius and A. Tuzhilin, "Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions," IEEE Transactions on Knowledge and Data Engineering, Vol.17, No.6, pp734-749, 2005.   DOI
6 R. Plutchik, "The Nature of Emotions," American Scientist, Vol.89, No.4, pp.344-350, 2001.   DOI
7 J. A. Russell, J. M. Fernabdez-Dols, A. S. R. Mastead, and J. C. Wellenkamp, Everyday Conceptions of Emotion: An introduction to the Psychology, Anthropology and Linguistics of Emotion, Kluwer Academic Publishers, 1995.
8 P. Ekman, Emotions and Life: Perspectives form Psychology, Biology, and Evolution, American Psychological Association, 2002.
9 윤애선, 권혁철, "감정 온톨로지의 구축을 위한 구성요소 분석," 인지과학, 제21권, 제1호, pp.157-175, 2010,
10 강상우, 박홍민, 서정연, "대화 시스템을 위한 사용자 발화 문장의 감정 분류," 인지과학, 제21권, 제4호, pp.459-480, 2010.
11 이상주, 맞춤형 콘텐츠 서비스를 위한 실시간 감성분석 및 공유기술, 첨단 융복합 콘텐츠 기술개발 연구보고서, 2013.
12 정현원, 나건, "감성 평가를 위한 감성의 의미 재 정립과 어휘 체계에 관한 연구," 대한인간공학회지, 제26권, 제3호, pp.17-25, 2007.
13 B. Liu, "Opinion Mining," ch.11 in Web Data Mining, Springer, 2006.
14 A. Esuli and F. Sebastiani, "SentiWordNet: A Publicly Available Lexical Resource for Opinion Mining," Proceedings of the 5th Conference on Language Resources and Evaluation(LREC'06), pp.417-422, 2006.
15 사사키 도시나오, 큐레이션 시대, 민음사, 2011.
16 조인호, LTE 시대의 콘텐츠 비즈니스 차별화 키워드: 큐레이션, KT경제경영연구소 동향보고서, 2013.
17 Bernett, "The Netflix Prize," KDD Cup and Workshop 2007.
18 Cremonesi, "Performance of recommender algorithms on top-n recommendation tasks," Proceedings of the 4th ACM conference on recommender systems, 2010.
19 Pearl Pu, Li Chen, and Rong Hu, "A User-Centric Evaluation Framework for Recommender Systems," Proceedings of the 5th ACM conference on recommender systems, 2011.