Evaluating interface variants on personality acquisition for recommender systems

G. Dunn, J. Wiersema, J.R.C. Ham, L.M. Aroyo

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

27 Citations (Scopus)
1 Downloads (Pure)

Abstract

Recommender systems help users find personally relevant media content in response to an overwhelming amount of this content available digitally. A prominent issue with recommender systems is recommending new content to new users; commonly referred to as the cold start problem. It has been argued that detailed user characteristics, like personality, could be used to mitigate cold start. To explore this solution, three alternative methods measuring users’ personality were compared to investigate which would be most suitable for user information acquisition. Participants (N = 60) provided user ease of use and satisfaction ratings to evaluate three different interface variants believed to measure participants’ personality characteristics. Results indicated that the NEO interface and the CFG interface were promising methods for measuring personality. Results are discussed in terms of potential benefits and broader implications for recommender systems.
Original languageEnglish
Title of host publication17th International Conference, UMAP 2009, formerly UM and AH, Trento, Italy, June 22-26, 2009
EditorsG.J. Houben, G. McCalla, F. Pianesi, M. Zancanaro
Place of PublicationBerlin
PublisherSpringer
Pages259-270
ISBN (Print)978-3-642-02246-3
DOIs
Publication statusPublished - 2009
Event17th International Conference on User Modelling, Adaptation, and Personalization (UMAP 2009) - Trento, Italy
Duration: 22 Jun 200926 Jun 2009
Conference number: 17

Publication series

NameLecture Notes in Computer Science
Volume5535
ISSN (Print)0302-9743

Conference

Conference17th International Conference on User Modelling, Adaptation, and Personalization (UMAP 2009)
Abbreviated titleUMAP 2010
CountryItaly
CityTrento
Period22/06/0926/06/09

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