Automatic Tracking of Changes in User Behavior to Support Proactivity in Pervasive Systems

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The ubiquity of Information and Communication Technologies (ICT) has led to a rapid growth of services offered to the user by the computer systems which become more and more pervasive. However, they remain complex requiring from the user a lot of effort in order to detect and choose the available service in the environment that meets the best his needs. We propose in this article to increase the proactivity of pervasive systems so that they can anticipate and provide personalized services to the user in the least intrusive manner. Our approach is based on the automatic generation of user preferences from the history of his interactions with the system. We propose, first, to detect user behaviors and contexts in which they appear based on historical experiences. Then we track in time the changes that may arise in these behaviors (appearance of a new behavior, change and forgetting of a behavior) to take into account in the proactive adaptation of the provided service.
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Pervasive Computing; Proactivity; Context Awareness; Personalisation; User Behavior Patterns Extraction

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