Browse > Article
http://dx.doi.org/10.5392/JKCA.2011.11.11.001

Personalized Dietary Nutrition Contents Recommendation using Hybrid Filtering for Managing Health  

Chung, Kyung-Yong (상지대학교 컴퓨터정보공학부)
Lee, Young-Ho (가천의과학대학교 의료공학부)
Publication Information
The Journal of the Korea Contents Association / v.11, no.11, 2011 , pp. 1-9 More about this Journal
Abstract
With the development of next IT convergence technology and the construction of infrastructure for personalized healthcare services, the importance of services based on user's preference is being spotlighted. Healthcare service have been progressed as treatment and management for specific diseases and dietary nutrition managements to customers according to the increase in chronic patients. In this paper, we proposed the personalized dietary nutrition contents recommendation using the hybrid filtering for managing health. The proposed method uses the hybrid filtering through combining the collaborative filtering and the image filtering in order to reinforce the special trend that recommendation provides similar contents. We developed the Web application for this purpose, and experimented with it to verify the logical validity and effectiveness. Accordingly, the satisfaction and the quality of services will be improved the healthcare by recommending the dietary nutrition contents. This evaluation found that the difference of satisfaction by service was statistically meaningful and showed high satisfaction.
Keywords
Preference; Nutrition Contents; Recommendation; Simulation; Collaborative Filtering; Chronic Patient;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 H. N. Kim, A. T. Jia, I. A. Haa, and G. S. Joa, "Collaborative Filtering based on Collaborative Tagging for Enhancing the Quality of Recommendation," J. of Electronic Commerce Research and Applications, Vol.9, Issue1, pp.73-83, 2010.   DOI   ScienceOn
2 P. Melville, R. J. Mooney, and R. Nagarajan, "Content-Boosted Collaborative Filtering for Improved Recommendations," Proc. of National Conference on Artificial Intelligence, pp.187-192, 2002.
3 J. L. Herlocker, J. A. Konstan, L. G. Terveen, and J. T. Riedl, "Evaluating Collaborative Filtering Recommender Systems," J. of ACM Trans. on Information Systems, Vol.22, No.1, pp.5-53, 2004.   DOI   ScienceOn
4 정경용, 조선문, "내용 기반 필터링을 위한 프로파일 학습에 의한 선호도 발견", 한국콘텐츠학회논문지, 제8권, 제2호, pp.1-8, 2008.   과학기술학회마을   DOI   ScienceOn
5 정경용, "이미지 기반 필터링을 이용한 개인화 아이템 추천", 한국콘텐츠학회논문지, 제8권, 제3호, pp.1-7, 2008.   과학기술학회마을   DOI   ScienceOn
6 정경용, "혼합 필터링과 연관 이웃 마이닝을 이용한 개인화 아이템 추천 기법", 인하대학교 컴퓨터정보공학과 박사학위논문, 2005.
7 K. Y. Chung, "Sensibility Ergonomics Fashion Recommendation System using Weather WebBot," Proc. of the International Conference on Information Science and Applications 2011, pp.712-717, IEEE Computer Society, 2011.
8 박동균, 김종훈, 김재권, 정은영, 이용호, "멀티플랫폼 환경의 만성 질환자 건강관리를 위한 유헬스 서비스 모델", 한국콘텐츠학회논문지, 제11권, 제8호, pp.23-32, 2011.   과학기술학회마을   DOI   ScienceOn
9 S. U. Jang, J. Y. Cho, K. S. Jeong, and G. S. Cho, "Exploring Possibilities of ECG Electrodes for Bio-monitoring Smartwear with Cu Sputtered Fabrics," J. of Human-Computer Interaction, Vol.4551, pp.1130-1137, 2007.
10 M. Jalali, N. Mustapha, Md. N. Sulaiman, A. Mamat, "WebPUM: A Web-based Recommendation System to Predict User Future Movements," J. of Expert Systems with Applications, Vol.37, Issue9, pp.6201-6212, 2010.   DOI   ScienceOn