Exploiting User Movements to Derive Recommendations in Large Facilities

  • Jürgen Dunkel
  • Ramón Hermoso
  • Florian Rückauf
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 801)


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.


Context-aware recommender systems Collaborative filtering Beacon technology 



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.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Jürgen Dunkel
    • 1
  • Ramón Hermoso
    • 2
  • Florian Rückauf
    • 1
  1. 1.Hannover University of Applied Sciences and ArtsHannoverGermany
  2. 2.University of ZaragozaZaragozaSpain

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