Item recommendation based on context-aware model for personalized u-healthcare service

Multimedia Tools and Applications

Volumn 71, Issue 2, 2014, Pages 855-872

  Kim, Jonghun ^a   Lee, Daesung ^b   Chung, Kyung Yong ^c  

^a BIT Computer Co   (South Korea)

^b Kyonggi University   (South Korea)

^c Sangji University   (South Korea)

Author keywords

Collaborative filtering; Context aware; Item recommendation; Personalized service; U healthcare service

Indexed keywords

COLLABORATIVE FILTERING; SEMANTICS;

CONTEXT-AWARE; CONTEXT-AWARE MODELS; EXISTING RECOMMENDATION SYSTEMS; ITEM RECOMMENDATION; PERSONALIZED SERVICE; RECOMMENDATION ACCURACY; U-HEALTHCARE SERVICES; UBIQUITOUS ENVIRONMENTS;

HEALTH CARE;

EID: 84903757959     PISSN: 13807501     EISSN: 15737721     Source Type: Journal    
DOI: 10.1007/s11042-011-0920-0     Document Type: Conference Paper

References (18)

1. Balabanovic M, Shoham Y (1997) Fab: content-based, collaborative recommendation. Communication of the Association of Computing Machinery 40(3):66-72
2. Breese JS, Kadie C (1998) Empirical analysis of predictive algorithms for collaborative filtering. Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence, Madison, WI, pp. 43-52
3. Brown PJ, Bovey JD, Chen X (1997) Context-aware application: From the laboratory to the marketplace. IEEE Personal Communication, pp. 58-64
4. Burchfield TR, Venkatesan S (2007) Accelerometer-based human abnormal movement detection in wireless sensor networks. In the 1st ACM SIGMOBILE international workshop on Systems and networking support for healthcare and assisted living environments San Juan, Puerto Rico
5. Gong L (2001) A software architecture for open service gateways. IEEE Internet Computing 5(1):64-70 (Pubitemid 32169173)
6. Good N, Schafer JB, Konstan JA, Borchers A, Sarwar B, Herlocker J, Riedl J (1999) Combining collaborative filtering with personal agents for better recommendations. Proceedings of the National Conference on Artificial Intelligence, pp. 439-446
7. Hidoc, http://www.hidoc.co.kr/HealthPedia
8. Jang S, Woo W (2003) ubi-UCAM: A unified context-aware application model. Context03, pp. 178-189 (Pubitemid 36769891)
9. Jeong K, Won J, Bae C (2008) User activity recognition and logging in distributed Intelligent Gadgets. In IEEE International Conferenceon Multi sensor Fusion and Integration for Intelligent Systems
10. Jung KY, Lee JH (2004) User preference mining through hybrid collaborative filtering and content-based filtering in recommendation system. IEICE Transaction on Information and Systems E87-D(12):2781-2790
11. Jung KY, Choi JH, Rim KW, Lee JH (2003) Development of design recommender system using collaborative filtering. LNCS 2911, Proceedings of the 6th International Conference of Asian Digital Libraries (ICADL'03), pp. 100-110
12. McDonald DW, Mark SA (2000) Expertise recommender: a Flexible recommendation system and architecture. Proceedings of the ACM Conference on Computer Supported Cooperative Work, pp. 231-240 (Pubitemid 32400054)
13. New Life Hypertension & Diabetes Clinic, http://www.goliving.co.kr
14. Rabiner LR (1989) A tutorial on hidden Markov models and selected application in speech recognition. In Proc IEEE 77(2):257-286
15. Ravi N, Dandekar N, Mysore P, Littman ML (2005) Activity recognition from accelerometer data. In American Association for Artificial Intelligence, pp. 11541-1546
16. Ungar LH, Foster DP (1998) Clustering methods for collaborative filtering. Proceedings of the Workshop on Recommendation Systems, pp. 114-129
17. Welltizen, http://neps.welltizen.com
18. Wojek C, Nickel K, Stiefelhagen R (2006) Activity recognition and room-level tracking in an office environment. in IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems Heidelberg, Germany