Communications of the ACM - Special issue on parallelism
Intelligent information-sharing systems
Communications of the ACM
Intelligent interfaces as agents
Intelligent user interfaces
A learning interface agent for scheduling meetings
IUI '93 Proceedings of the 1st international conference on Intelligent user interfaces
Experience with a learning personal assistant
Communications of the ACM
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Machine Learning
Varying the user interaction within multi-agent systems
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Web Search Using a Genetic Algorithm
IEEE Internet Computing
Machine Learning and Intelligent Agents
Machine Learning and Its Applications, Advanced Lectures
Hi-index | 0.00 |
Interface agents are being developed to assist users with a variety of tasks. To perform effectively, such agents need knowledge of user preferences. An agent architecture has been developed which observes a user performing tasks, and identifies features which can be used as training data by a learning algorithm. Using the learned profile, an agent can give advice to the user on dealing with new situations. The architecture has been applied to two different information filtering domains: classifying incoming mail messages (Magi) and identifying interesting USENet news articles (UNA). This paper describes the architecture and examines the results of experimentation with different learning algorithms and different feature extraction strategies within these domains.