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2005
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(2005): Active affective State detection and user assistance with dynamic bayesian networks. In: IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 35 (1), S. 93-105. DOI: 10.1109/TSMCA.2004.838454
DOI: https://doi.org/10.1109/TSMCA.2004.838454 Abstract: With the rapid development of pervasive and ubiquitous computing applications, intelligent user-assistance systems face challenges of ambiguous, uncertain, and multimodal sensory observations, user’s changing state, and various constraints on available resources and costs in making decisions. We introduce a new probabilistic framework based on the dynamic Bayesian networks (DBNs) to dynamically model and recognize user’s affective states and to provide the appropriate assistance in order to keep user in a productive state. We incorporate an active sensing mechanism into the DBN framework to perform purposive and sufficing information integration in order to infer user’s affective state and to provide correct assistance in a timely and efficient manner. Experiments involving both synthetic and real data demonstrate the feasibility of the proposed framework as well as the effectiveness of the proposed active sensing strategy.
Keywords: active affective state detection, active fusion, active sensing mechanism, affective state detection, Angemessen(heit) (von Technik), Bayesian methods, Bayesian networks (BNs), belief networks, Context modeling, Costs, dynamic Bayesian networks, Face detection, ieee xplore, information integration, Information theory, Intelligent networks, Intelligent sensors, Intelligent Systems, intelligent user assistance system, probabilistic framework, sensor fusion, Systems engineering, theory, Ubiquitous computing, user assistance, user interfaces
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