Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
C4.5: programs for machine learning
C4.5: programs for machine learning
Learning and Revising User Profiles: The Identification ofInteresting Web Sites
Machine Learning - Special issue on multistrategy learning
A hybrid user model for news story classification
UM '99 Proceedings of the seventh international conference on User modeling
The development of behavior-based user models for a computer system
UM '99 Proceedings of the seventh international conference on User modeling
Patterns of search: analyzing and modeling Web query refinement
UM '99 Proceedings of the seventh international conference on User modeling
User modeling in adaptive interfaces
UM '99 Proceedings of the seventh international conference on User modeling
Fril- Fuzzy and Evidential Reasoning in Artificial Intelligence
Fril- Fuzzy and Evidential Reasoning in Artificial Intelligence
Human-centred Intelligent Systems and Soft Computing
BT Technology Journal
Preface to UMUAI Special Issue on MachineLearning for User Modeling
User Modeling and User-Adapted Interaction
Logic-Based Representation and Reasoning for User Modeling Shell Systems
User Modeling and User-Adapted Interaction
A Machine-Learning Apprentice for the Completion of Repetitive Forms
IEEE Expert: Intelligent Systems and Their Applications
Machine Learning
The Intelligent Assistant: An Overview
Intelligent Systems and Soft Computing: Prospects, Tools and Applications
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
| Hi-index | 0.00 |
With the burgeoning complexity and capabilities of modern information appliances and services, user modelling is becoming an increasingly important research area. Simple user profiles already personalise many software products and consumer goods such as digital TV recorders and mobile phones. A user model should be easy to initialise, and it must adapt in the light of interaction with the user. In many cases, a large amount of training data is needed to generate a user model, and adaptation is equivalent to retraining the system. This paper briefly outlines the user modelling problem and work done at BTexact on an Intelligent Personal Assistant (IPA) which incorporates a user profile. We go on to describe FILUM, a more flexible method of user modelling, and show its application to the Telephone Assistant component of the IPA, with tests to illustrate its usefulness.