Dynamically-optimized context in recommender systems
Proceedings of the 6th international conference on Mobile data management
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IEEE Intelligent Systems
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Review: Personalizing recommendations for tourists
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UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
Effect of the number of users and bias of users' preference on recommender systems
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
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OTM'05 Proceedings of the 2005 OTM Confederated international conference on On the Move to Meaningful Internet Systems
Location-based service with context data for a restaurant recommendation
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Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
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International Journal of Handheld Computing Research
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A recommender agent in mobile environments shouldbe context-aware to assist users while the users aremoving. Many different kinds of contexts can be used by arecommender agent, such as weather, route conditions,time and location, etc. In this paper, we demonstrate aprototype design of a software agent that recommendstravel-related information according to contexts of theuser in mobile environment. The recommendationprocedure includes the dialogue between the user and theagent for modifying constraints given to the agent. Weillustrate with a scenario of recommending a restaurant toa tourist in Taipei city by interacting with a personalizedagent in a mobile device.