Recommending rides: psychometric profiling in the theme park

This paper presents a study intended to inform the design of a recommender system for theme park rides. It examines the efficacy of psychometric testing for profiling theme park visitors, with the aim of establishing a set of measures to be included in a visitor profile intended for use in a collabo...

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Main Authors: Rennick-Egglestone, Stefan, Whitbrook, Amanda, Greensmith, Julie, Walker, Brendan, Benford, Steve, Marshall, Joe, Kirk, David, Schnädelbach, Holger, Irune, Ainoje, Rowland, Duncan
Format: Article
Published: ACM 2010
Online Access:https://eprints.nottingham.ac.uk/1561/
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author Rennick-Egglestone, Stefan
Whitbrook, Amanda
Greensmith, Julie
Walker, Brendan
Benford, Steve
Marshall, Joe
Kirk, David
Schnädelbach, Holger
Irune, Ainoje
Rowland, Duncan
author_facet Rennick-Egglestone, Stefan
Whitbrook, Amanda
Greensmith, Julie
Walker, Brendan
Benford, Steve
Marshall, Joe
Kirk, David
Schnädelbach, Holger
Irune, Ainoje
Rowland, Duncan
author_sort Rennick-Egglestone, Stefan
building Nottingham Research Data Repository
collection Online Access
description This paper presents a study intended to inform the design of a recommender system for theme park rides. It examines the efficacy of psychometric testing for profiling theme park visitors, with the aim of establishing a set of measures to be included in a visitor profile intended for use in a collaborative recommender system. Results presented in this paper highlight the predictive value of a number of psychometric measures, including two drawn from the ―Big Five‖ personality inventory, and one drawn from the ―Sensation Seeking Scale‖. The paper discusses general research challenges associated with the integration of psychometric testing into recommender systems, and describes planned future work on a theme park recommender system.
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publishDate 2010
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spelling nottingham-15612020-05-04T16:29:55Z https://eprints.nottingham.ac.uk/1561/ Recommending rides: psychometric profiling in the theme park Rennick-Egglestone, Stefan Whitbrook, Amanda Greensmith, Julie Walker, Brendan Benford, Steve Marshall, Joe Kirk, David Schnädelbach, Holger Irune, Ainoje Rowland, Duncan This paper presents a study intended to inform the design of a recommender system for theme park rides. It examines the efficacy of psychometric testing for profiling theme park visitors, with the aim of establishing a set of measures to be included in a visitor profile intended for use in a collaborative recommender system. Results presented in this paper highlight the predictive value of a number of psychometric measures, including two drawn from the ―Big Five‖ personality inventory, and one drawn from the ―Sensation Seeking Scale‖. The paper discusses general research challenges associated with the integration of psychometric testing into recommender systems, and describes planned future work on a theme park recommender system. ACM 2010-12-01 Article PeerReviewed Rennick-Egglestone, Stefan, Whitbrook, Amanda, Greensmith, Julie, Walker, Brendan, Benford, Steve, Marshall, Joe, Kirk, David, Schnädelbach, Holger, Irune, Ainoje and Rowland, Duncan (2010) Recommending rides: psychometric profiling in the theme park. Computers in Entertainment, 8 (3). http://doi.acm.org/10.1145/1902593.1902600 doi:10.1145/1902593.1902600 doi:10.1145/1902593.1902600
spellingShingle Rennick-Egglestone, Stefan
Whitbrook, Amanda
Greensmith, Julie
Walker, Brendan
Benford, Steve
Marshall, Joe
Kirk, David
Schnädelbach, Holger
Irune, Ainoje
Rowland, Duncan
Recommending rides: psychometric profiling in the theme park
title Recommending rides: psychometric profiling in the theme park
title_full Recommending rides: psychometric profiling in the theme park
title_fullStr Recommending rides: psychometric profiling in the theme park
title_full_unstemmed Recommending rides: psychometric profiling in the theme park
title_short Recommending rides: psychometric profiling in the theme park
title_sort recommending rides: psychometric profiling in the theme park
url https://eprints.nottingham.ac.uk/1561/
https://eprints.nottingham.ac.uk/1561/
https://eprints.nottingham.ac.uk/1561/