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Licensed Unlicensed Requires Authentication Published by Oldenbourg Wissenschaftsverlag April 1, 2015

Item Familiarity as a Possible Confounding Factor in User-Centric Recommender Systems Evaluation

Dietmar Jannach, Lukas Lerche and Michael Jugovac
From the journal i-com

Abstract

User studies play an important role in academic research in the field of recommender systems as they allow us to assess quality factors other than the predictive accuracy of the underlying algorithms. User satisfaction is one such factor that is often evaluated in laboratory settings and in many experimental designs one task of the participants is to assess the suitability of the system-generated recommendations. The effort required by the user to make such an assessment can, however, depend on the user’s familiarity with the presented items and directly impact on the reported user satisfaction. In this paper, we report the results of a preliminary recommender systems user study using Mechanical Turk, which indicates that item familiarity is strongly correlated with overall satisfaction.

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Published Online: 2015-04-01
Published in Print: 2015-04-15

© 2015 Walter de Gruyter GmbH, Berlin/Boston