Experience with a learning personal assistant
Communications of the ACM
Predicting UNIX Command Lines: Adjusting to User Patterns
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Model-based evaluation of cell phone menu interaction
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
EMMA: modèle utilisateur pour la plasticité des interfaces homme-machine en mobilité
UbiMob '08 Proceedings of the 4th French-speaking conference on Mobility and ubiquity computing
Learning Key Contexts of Use in the Wild for Driving Plastic User Interfaces Engineering
HCSE-TAMODIA '08 Proceedings of the 2nd Conference on Human-Centered Software Engineering and 7th International Workshop on Task Models and Diagrams
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Mobile phones are becoming a popular platform for a range of applications. However, due to size restrictions, the interfaces of these applications can be difficult to use. Customising an interface for a particular user offers the potential to improve an interface’s efficiency. In this paper, we propose customising a mobile phone’s Profile application. We apply a machine learning approach to discover concepts that describe a user’s profile-activations in terms of their scheduled appointments. We found that it is possible to learn useful concepts, which maybe used to improve the users interaction with mobile phone devices.