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Author Irune, Ainoje ♦ Whitbrook, Amanda ♦ Egglestone, Stefan Rennick ♦ Benford, Steve ♦ Walker, Brendan ♦ Rowland, Duncan ♦ Marshall, Joe ♦ Kirk, David ♦ Greensmith, Julie ♦ Schnädelbach, Holger
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Keyword Personal profiling ♦ Theme park ♦ Fairground ♦ Psychometric profiling ♦ Collaborative recommendation ♦ Recommender systems
Abstract This article 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 article 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 article 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.
Description Affiliation: BAE Systems (Whitbrook, Amanda) || Aerial (Walker, Brendan) || University of Nottingham (Egglestone, Stefan Rennick; Greensmith, Julie; Benford, Steve; Marshall, Joe; Kirk, David; Schnädelbach, Holger; Irune, Ainoje; Rowland, Duncan)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2008-03-01
Publisher Place New York
Journal Computers in Entertainment (CIE) (CIE)
Volume Number 8
Issue Number 3
Page Count 17
Starting Page 1
Ending Page 17


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Source: ACM Digital Library