Chapter

User Modeling, Adaption and Personalization

Volume 6787 of the series Lecture Notes in Computer Science pp 281-292

Personalizing the Theme Park: Psychometric Profiling and Physiological Monitoring

  • Stefan Rennick-EgglestoneAffiliated withCarnegie Mellon UniversitySchool of Computer Science, University of Nottingham
  • , Amanda WhitbrookAffiliated withCarnegie Mellon UniversityBAE Systems, Systems Engineering Innovation Centre, University of Loughborough
  • , Caroline LeygueAffiliated withCarnegie Mellon UniversityHorizon Digital Economy Research, Sir Colin Campbell Building, University of Nottingham
  • , Julie GreensmithAffiliated withCarnegie Mellon UniversitySchool of Computer Science, University of Nottingham
  • , Brendan WalkerAffiliated withCarnegie Mellon UniversityAerial
  • , Steve BenfordAffiliated withCarnegie Mellon UniversitySchool of Computer Science, University of Nottingham
  • , Holger SchnädelbachAffiliated withCarnegie Mellon UniversitySchool of Computer Science, University of Nottingham
  • , Stuart ReevesAffiliated withCarnegie Mellon UniversityHorizon Digital Economy Research, Sir Colin Campbell Building, University of Nottingham
  • , Joe MarshallAffiliated withCarnegie Mellon UniversitySchool of Computer Science, University of Nottingham
    • , David KirkAffiliated withCarnegie Mellon UniversitySchool of Computer Science, University of Nottingham
    • , Paul TennentAffiliated withCarnegie Mellon UniversitySchool of Computer Science, University of Nottingham
    • , Ainoje IruneAffiliated withCarnegie Mellon UniversitySchool of Computer Science, University of Nottingham
    • , Duncan RowlandAffiliated withCarnegie Mellon UniversitySchool of Computer Science, University of Lincoln

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Abstract

Theme parks are important and complex forms of entertainment, with a broad user-base, and with a substantial economic impact. In this paper, we present a case study of an existing theme park, and use this to motivate two research challenges in relation to user-modeling and personalization in this environment: developing recommender systems to support theme park visits, and developing rides that are personalized to the users who take part in them. We then provide an analysis, drawn from a real-world study on an existing ride, which illustrates the efficacy of psychometric profiling and physiological monitoring in relation to these challenges. We conclude by discussing further research work that could be carried out within the theme park, but motivate this research by considering the broader contribution to user-modeling issues that it could make. As such, we present the theme park as a microcosm which is amenable to research, but which is relevant in a much broader setting.

Keywords

Psychometrics physiological monitoring theme park