Abstract
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.
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Şerban, G., Tarţa, A., Moldovan, G.S. (2007). A Learning Interface Agent for User Behavior Prediction. In: Jacko, J.A. (eds) Human-Computer Interaction. HCI Intelligent Multimodal Interaction Environments. HCI 2007. Lecture Notes in Computer Science, vol 4552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73110-8_55
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DOI: https://doi.org/10.1007/978-3-540-73110-8_55
Publisher Name: Springer, Berlin, Heidelberg
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