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Leveraging Interfaces to Improve Recommendation Diversity

Tsai, Chun-Hua and Brusilovsky, Peter (2017) Leveraging Interfaces to Improve Recommendation Diversity. In: Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization, 09 July 2017 - 12 July 2017, Bratislava, Slovakia.

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Abstract

Increasing diversity in the output of a recommender system is an active research question for solving a long-tail issue. Most of the current approaches have focused on ranked list optimization to improve recommendation diversity. However, little is known about the effect that a visual interface can have on this issue. This paper shows that a multidimensional visualization promotes diversity of social exploration in the context of an academic conference. Our study shows a significant difference in the exploration pattern between ranked list and visual interfaces. The results show that a visual interface can help the user explore a a more diverse set of recommended items.


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Details

Item Type: Conference or Workshop Item (Paper)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Tsai, Chun-Huacht77@pitt.eduCHT77
Brusilovsky, Peterpeterb@pitt.eduPETERB
Date: 2017
Date Type: Publication
Publisher: ACM
Place of Publication: New York, NY, USA
Page Range: 65 - 70
Event Title: Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization
Event Dates: 09 July 2017 - 12 July 2017
Event Type: Conference
Refereed: Yes
Uncontrolled Keywords: explanation, social, recommendation, transparency, user, control
Official URL: http://doi.acm.org/10.1145/3099023.3099073
Date Deposited: 09 Aug 2017 15:13
Last Modified: 25 Aug 2017 04:55
URI: http://d-scholarship.pitt.edu/id/eprint/32810

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