A Bayesian model of plan recognition
Artificial Intelligence
Agents that reduce work and information overload
Communications of the ACM
Finding interesting rules from large sets of discovered association rules
CIKM '94 Proceedings of the third international conference on Information and knowledge management
Principles of mixed-initiative user interfaces
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
A User Modeling Approach to Determining System Initiative in Mixed-Initiative AI Systems
UM '01 Proceedings of the 8th International Conference on User Modeling 2001
User - interface agent interaction: personalization issues
International Journal of Human-Computer Studies
IEEE Intelligent Systems
The lumière project: Bayesian user modeling for inferring the goals and needs of software users
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
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A key aspect when interface agents provide personalized assistance to users, is knowing not only a user's preferences and interests with respect to a software application but also when and how the user prefers to be assisted. To achieve this goal, interface agents have to detect the user's intention to determine when to assist the user, and the user's interaction and interruption preferences to provide the right type of assistance at the right time. In this work we describe a user profiling approach that considers these issues within a user profile, which enables the agent to choose the best type of assistance for a given user in a given situation. We also describe the results obtained when evaluating our proposal in a calendar application.