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Discovering frequent user--environment interactions in intelligent environments

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Abstract

Intelligent Environments are expected to act proactively, anticipating the user’s needs and preferences. To do that, the environment must somehow obtain knowledge of those need and preferences, but unlike current computing systems, in Intelligent Environments, the user ideally should be released from the burden of providing information or programming any device as much as possible. Therefore, automated learning of a user’s most common behaviors becomes an important step towards allowing an environment to provide highly personalized services. In this article, we present a system that takes information collected by sensors as a starting point and then discovers frequent relationships between actions carried out by the user. The algorithm developed to discover such patterns is supported by a language to represent those patterns and a system of interaction that provides the user the option to fine tune their preferences in a natural way, just by speaking to the system.

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Notes

  1. http://www.freetts.sourceforge.net/docs/index.php.

  2. http://www.cmusphinx.sourceforge.net/sphinx4/.

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Acknowledgments

Craig Wootton and Michael McTear provided initial guidance on available technologies for voice processing. This work was partially supported by Basque Government grant PC2008-28B.

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Authors and Affiliations

  1. University of Mondragon, Mondragon, Spain

    Asier Aztiria, Rosa Basagoiti & Alberto Izaguirre

  2. University of Ulster, Jordanstown, UK

    Juan Carlos Augusto

  3. Washington State University, Pullman, WA, USA

    Diane J. Cook

Authors
  1. Asier Aztiria
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  2. Juan Carlos Augusto
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  3. Rosa Basagoiti
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  4. Alberto Izaguirre
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  5. Diane J. Cook
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Corresponding author

Correspondence to Asier Aztiria.

Appendix: language specification

Appendix: language specification

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Aztiria, A., Augusto, J.C., Basagoiti, R. et al. Discovering frequent user--environment interactions in intelligent environments. Pers Ubiquit Comput 16, 91–103 (2012). https://doi.org/10.1007/s00779-011-0471-4

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  • DOI: https://doi.org/10.1007/s00779-011-0471-4

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