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Comparison of Machine Learning Techniques for Bayesian Networks for User-Adaptive Systems

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Book cover Resource-Adaptive Cognitive Processes

Part of the book series: Cognitive Technologies ((COGTECH))

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Abstract

During the last decade, Bayesian networks (BNs) have been one of the major research topics in the AI community in the area of reasoning under uncertainty. The READY project has been one of the forerunners along these lines – in particular regarding the application of BNs in the context of user modeling/user-adaptive systems (UASs) over the whole period of the collaborative research program 378.

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Authors and Affiliations

  1. SAP AG, Neue Bahnhofstr. 21, D-66386, St. Ingbert, Germany

    Frank Wittig

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  1. Frank Wittig
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Correspondence to Frank Wittig .

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Editors and Affiliations

  1. Inst. Computerlinguistik, Universität des Saarlandes, Saarbrücken, 66041, Germany

    Matthew W. Crocker

  2. Deutsches Forschungszentrum für, Künstliche Intelligenz, Universität des Saarlandes, Stuhlsatzenhausweg 3, Saarbrücken, 66123, Germany

    Jörg Siekmann

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Wittig, F. (2010). Comparison of Machine Learning Techniques for Bayesian Networks for User-Adaptive Systems. In: Crocker, M., Siekmann, J. (eds) Resource-Adaptive Cognitive Processes. Cognitive Technologies. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89408-7_14

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  • DOI: https://doi.org/10.1007/978-3-540-89408-7_14

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89407-0

  • Online ISBN: 978-3-540-89408-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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