Analysis of user behaviour as time series
HCI'92 Proceedings of the conference on People and computers VII
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Human-computer interaction (2nd ed.)
Human-computer interaction (2nd ed.)
Experiments in UNIX command prediction
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
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Predicting user behavior is an important issue in Human Computer Interaction ([5]) research, having an essential role when developing intelligent user interfaces. A possible solution to deal with this challenge is to build an intelligent interface agent ([8]) that learns to identify patterns in users behavior. The aim of this paper is to introduce a new agent based approach in predicting users behavior, using a probabilistic model. We propose an intelligent interface agent that uses a supervised learning technique in order to achieve the desired goal. We have used Aspect Oriented Programming ([7]) in the development of the agent in order to benefit of the advantages of this paradigm. Based on a newly defined evaluation measure, we have determined the accuracy of the agent's prediction on a case study.