Learning users' interests by unobtrusively observing their normal behavior
Proceedings of the 5th international conference on Intelligent user interfaces
A reinforcement learning agent for personalized information filtering
Proceedings of the 5th international conference on Intelligent user interfaces
Understanding and Using Context
Personal and Ubiquitous Computing
Context-Aware Computing: A Test Case
UbiComp '02 Proceedings of the 4th international conference on Ubiquitous Computing
Journal of Systems and Software
A component-based approach for adaptive dynamic web documents
Journal of Web Engineering
An approach to user-behavior-aware web applications
ICWE'05 Proceedings of the 5th international conference on Web Engineering
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With the considerable amount of data and the diversity of the user's needs, the personalization of information becomes a real challenge in web-based information systems. This paper presents a personalized access technique, based on a profile modeling. This technique requires two steps: 1) building user's profile and 2) using profile content for filtering information. The first step consists in modeling a global profile which can be used for different and independent requirements of personalization. The profile modeling takes into account the user's context when defining user's profiles. We describe a global profile in three levels: meta-description level, description level for a specific domain, instances (data). The second step consists in selecting the profiles rules which correspond to the user and his current context and to filter information accordingly.