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Exploiting User Movements to Derive Recommendations in Large Facilities

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Distributed Computing and Artificial Intelligence, Special Sessions, 15th International Conference (DCAI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 801))

Abstract

This paper provides an innovative approach for taking advantage of user’s movement data as implicit user feedback for deriving recommendations in large facilities. By means of a real-world museum scenario a beacon infrastructure for tracking sojourn times is presented. Then we show how sojourn times can be integrated in a collaborative filtering algorithm approach in order to outcome accurate recommendations.

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Notes

  1. 1.

    https://www.landesmuseum-hannover.niedersachsen.de/.

  2. 2.

    https://developer.apple.com/ibeacon/.

  3. 3.

    https://developers.google.com/beacons/.

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Acknowledgments

This work has been supported by the projects DGA-FSE, TIN2015-65515-C4-4-R, TIN2016-78011-C4-3-R and Universidad de Zaragoza - Ibercaja-CAI fellowship IT 9/17.

Author information

Authors and Affiliations

  1. Hannover University of Applied Sciences and Arts, Hannover, Germany

    Jürgen Dunkel & Florian Rückauf

  2. University of Zaragoza, Zaragoza, Spain

    Ramón Hermoso

Authors
  1. Jürgen Dunkel
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  2. Ramón Hermoso
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  3. Florian Rückauf
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Corresponding author

Correspondence to Jürgen Dunkel .

Editor information

Editors and Affiliations

  1. BISITE Digital Innovation Hub, University of Salamanca, Salamanca, Spain

    Sara Rodríguez

  2. BISITE Digital Innovation Hub, University of Salamanca, Salamanca, Spain

    Javier Prieto

  3. GECAD - Instituto Superior de Engenharia, Porto, Portugal

    Pedro Faria

  4. Department of Computer Science and Production Management, University of Zielona Góra, Zielona Góra, Poland

    Sławomir Kłos

  5. Computing Science and Artificial Intelligence, Rey Juan Carlos University, Móstoles, Madrid, Spain

    Alberto Fernández

  6. Basque Center for Applied Mathematics, Bilbao, Spain

    Santiago Mazuelas

  7. Basque Center for Applied Mathematics, Universidad de Alcalá, Alcalá de Henares, Spain

    M. Dolores Jiménez-López

  8. Departamento de Informática y Automática, University of Salamanca, Salamanca, Spain

    María N. Moreno

  9. Departamento de Sistemas Informáticos, University of Castilla-La Mancha, Albacete, Spain

    Elena M. Navarro

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Dunkel, J., Hermoso, R., Rückauf, F. (2019). Exploiting User Movements to Derive Recommendations in Large Facilities. In: Rodríguez, S., et al. Distributed Computing and Artificial Intelligence, Special Sessions, 15th International Conference. DCAI 2018. Advances in Intelligent Systems and Computing, vol 801. Springer, Cham. https://doi.org/10.1007/978-3-319-99608-0_14

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