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Enhancing recommendation diversity through a dual recommendation interface

UNSPECIFIED (2017) Enhancing recommendation diversity through a dual recommendation interface. In: UNSPECIFIED.

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Abstract

The beyond-relevance objectives of recommender system are drawing more and more attention. For example, a diversity-enhanced interface has been shown to positively associate with overall levels of user satisfaction. However, little is known about how a diversity-enhanced interface can help users to accomplish various real-world tasks. In this paper, we present a visual diversity-enhanced interface that presents recommendations in a two-dimensional scatter plot. Our goal was to design a recommender system interface to explore the different relevance prospects of recommended items in parallel and to stress their diversity. A within-subject user study with real-life tasks was conducted to compare our visual interface to a standard ranked list interface. Our user study results show that the visual interface significantly reduced exploration efforts required for explored tasks. Also, the users' subjective evaluation shows significant improvement on many user-centric metrics. We show that the users explored a diverse set of recommended items while experiencing an improvement in overall user satisfaction.


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Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Date: 1 January 2017
Date Type: Publication
Journal or Publication Title: CEUR Workshop Proceedings
Volume: 1884
Page Range: 10 - 15
Event Type: Conference
Schools and Programs: School of Computing and Information > Information Science
Refereed: Yes
ISSN: 1613-0073
Date Deposited: 31 Jul 2018 16:28
Last Modified: 08 Jan 2019 22:55
URI: http://d-scholarship.pitt.edu/id/eprint/35049

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