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Conference Paper
A Dual-Layer User Model based Cognitive System for User-adaptive Service Robots
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- Authors
- Seong-Yong Koo, Kiru Park, Hyun Kim, Dong-Soo Kwon
- Issue Date
- 2011-07
- Citation
- International Symposium on Robot and Human Interactive Communication (RO-MAN) 2011, pp.59-64
- Language
- English
- Type
- Conference Paper
- Abstract
- This paper proposes a dual-layer user model to generate descriptive service recommendations for user-adaptive service robots. The user model represents user preferences as the associative memory in the bottom-layer and association rules in the top-layer. The learning and inference processes in the two layers, and the bottom-up rule extraction process, are explained. The proposed user model was applied to a user-adaptive coffee menu recommendation system, and the quantitative and qualitative performances of the user-adaptive and descriptive recommendation system were evaluated by comparison with non-descriptive and random recommendation methods. © 2011 IEEE.
- KSP Keywords
- Bottom-Up, Cognitive system, Dual layer, Extraction process, Recommendation system, Rule extraction, Service robots, User Model, User preference, adaptive service, association rules