Experiences of developing and deploying a context-aware tourist guide: the GUIDE project
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Personalized location-based brokering using an agent-based intermediary architecture
Decision Support Systems - Special issue: Agents and e-commerce business models
Context-Awareness on Mobile Devices - the Hydrogen Approach
HICSS '03 Proceedings of the 36th Annual Hawaii International Conference on System Sciences (HICSS'03) - Track 9 - Volume 9
PILGRIM: A Location Broker and Mobility-Aware Recommendation System
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
The attraction of personalized service for users in mobile commerce: an empirical study
ACM SIGecom Exchanges - Mobile commerce
Location management for mobile commerce applications in wireless Internet environment
ACM Transactions on Internet Technology (TOIT)
A Personalized Restaurant Recommender Agent for Mobile E-Service
EEE '04 Proceedings of the 2004 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'04)
Design iterations for a location-aware event planner
Personal and Ubiquitous Computing
VISCORS: A Visual-Content Recommender for the Mobile Web
IEEE Intelligent Systems
Contextual recommendation based on text mining
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Fulfilling mobile information needs: a study on the use of mobile phones
Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication
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Recently, there has been a significant increase in the use of data via the mobile web. Since the user interfaces for mobile devices are inconvenient for browsing through many pages and searching their contents, many studies have focused on ways to recommend content or menus that users prefer. However, the mobile usage pattern of content or services differs according to context. In this paper, we apply context information—location, time, identity, activity, and device—to recommend services or content on the mobile web. A Korean mobile service provider has implemented context-aware recommendations. The usage logs of this service are analyzed to show the performance of context-aware recommendations.