An Evidential and Context-Aware Recommendation Strategy to Enhance Interactions with Smart Spaces

  • Josué Iglesias
  • Ana M. Bernardos
  • José R. Casar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8073)

Abstract

This work describes a novel strategy implementing a context-aware recommendation system. It has been conceived to offer an intelligent selection of micro-services used to orchestrate networks of smart objects taking into account users’ needs and preferences. The recommendation offering dynamically evolves depending on users’ micro-service management patterns and users’ context. The complete system has been designed within Dempster-Shafer evidential theory framework, ensuring uncertainty support both at context acquisition and at recommendation configuration level.

Keywords

Dempster-Shafer evidential theory context-aware services recommendation systems smart spaces smart objects 

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References

  1. 1.
    Bernardos, A.M., Casar, J.R., Cano, J., Bergesio, L.: Enhancing interaction with smart objects through mobile devices. In: Proceedings of the 9th ACM International Symposium on Mobility Management and Wireless Access, MobiWac 2011, pp. 199–202. ACM, New York (2011)Google Scholar
  2. 2.
    Adomavicius, G., Tuzhilin, A.: Context-aware recommender systems. In: ACM Conference on Recommender Systems, pp. 335–336 (2008)Google Scholar
  3. 3.
    Hong, X., Nugent, C., Mulvenna, M., McClean, S., Scotney, B., Devlin, S.: Evidential fusion of sensor data for activity recognition in smart homes. Pervasive and Mobile Computing 5(3), 236–252 (2009)CrossRefGoogle Scholar
  4. 4.
    McKeever, S., Ye, J., Coyle, L., Dobson, S.: Using dempster-shafer theory of evidence for situation inference. In: Barnaghi, P., Moessner, K., Presser, M., Meissner, S. (eds.) EuroSSC 2009. LNCS, vol. 5741, pp. 149–162. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  5. 5.
    Casanovas, M., Merigó, J.M.: Fuzzy aggregation operators in decision making with dempster shafer belief structure. Expert Systems with Applications 39, 7138–7149 (2012)CrossRefGoogle Scholar
  6. 6.
    Liu, W., Hughes, J.G., McTear, M.F.: Advances in the dempster-shafer theory of evidence, pp. 441–471. John Wiley & Sons, Inc., New York (1994)Google Scholar
  7. 7.
    Tolstikov, A., Hong, X., Biswas, J., Nugent, C., Chen, L., Parente, G.: Comparison of fusion methods based on dst and dbn in human activity recognition. Journal of Control Theory and Applications 9, 18–27 (2011)CrossRefGoogle Scholar
  8. 8.
    Shafer, G.: A Mathematical Theory of Evidence. Princeton University Press, Princeton (1976)MATHGoogle Scholar
  9. 9.
    Sentz, K., Ferson, S.: Combination of evidence in dempster-shafer theory. Technical report, Sandia National Laboratories, SAND 2002-0835 (2002)Google Scholar
  10. 10.
    Savage, L.J.: The theory of statistical decision. Journal of the American Statistical Association 46(253), 55–67 (1951)MATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Josué Iglesias
    • 1
  • Ana M. Bernardos
    • 1
  • José R. Casar
    • 1
  1. 1.Telecommunications SchoolUniversidad Politécnica de MadridMadridSpain

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