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Beyond the ranked list: User-driven exploration and diversification of social recommendation

Tsai, CH and Brusilovsky, P (2018) Beyond the ranked list: User-driven exploration and diversification of social recommendation. In: UNSPECIFIED.

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Abstract

The beyond-relevance objectives of recommender systems have been drawing more and more attention. For example, a diversity-enhanced interface has been shown to associate positively with overall levels of user satisfaction. However, little is known about how users adopt diversity-enhanced interfaces to accomplish various real-world tasks. In this paper, we present two attempts at creating a visual diversity-enhanced interface that presents recommendations beyond a simple ranked list. Our goal was to design a recommender system interface to help users explore the different relevance prospects of recommended items in parallel and to stress their diversity. Two within-subject user studies in the context of social recommendation at academic conferences were conducted to compare our visual interfaces. Results from our user study show that the visual interfaces significantly reduced the exploration efforts required for given tasks and helped users to perceive the recommendation diversity. We show that the users examined a diverse set of recommended items while experiencing an improvement in overall user satisfaction. Also, the users' subjective evaluations show significant improvement in many user-centric metrics. Experiences are discussed that shed light on avenues for future interface designs.


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Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Tsai, CHcht77@pitt.eduCHT770000-0001-9188-0362
Brusilovsky, Ppeterb@pitt.eduPETERB0000-0002-1902-1464
Date: 5 March 2018
Date Type: Publication
Journal or Publication Title: International Conference on Intelligent User Interfaces, Proceedings IUI
Page Range: 239 - 250
Event Type: Conference
DOI or Unique Handle: 10.1145/3172944.3172959
Schools and Programs: School of Computing and Information > Information Science
Refereed: Yes
ISBN: 9781450349451
Date Deposited: 25 Jul 2018 12:35
Last Modified: 27 Mar 2021 10:55
URI: http://d-scholarship.pitt.edu/id/eprint/35007

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