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Scalable Exploration of Relevance Prospects to Support Decision Making

Verbert, Katrien and Seipp, Karsten and He, Chen and Parra, Denis and Wongchokprasitti, Chirayu and Brusilovsky, Peter (2016) Scalable Exploration of Relevance Prospects to Support Decision Making. In: Joint Workshop on Interfaces and Human Decision Making for Recommender Systems at 10th ACM Conference on Recommender Systems, 16 Sep 2016, Boston, MA, USA.

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Abstract

Recent efforts in recommender systems research focus increasingly on human factors that affect acceptance of recommendations, such as user satisfaction, trust, transparency, and user control. In this paper, we present a scalable visualisation to interleave the output of several recommender engines with human-generated data, such as user bookmarks and tags. Such a visualisation enables users to explore which recommendations have been bookmarked by like-minded members of the community or marked with a specific relevant tag. Results of a preliminary user study (N=20) indicate that effectiveness and probability of item selection increase when users can explore relations between multiple recommendations and human feedback. In addition, perceived effectiveness and actual effectiveness of the recommendations as well as user trust into the recommendations are higher than a traditional list representation of recommendations.


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Details

Item Type: Conference or Workshop Item (Paper)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Verbert, Katrien
Seipp, Karsten
He, Chen
Parra, Denis0000-0001-9878-8761
Wongchokprasitti, Chirayu
Brusilovsky, Peterpeterb@pitt.eduPETERB0000-0002-1902-1464
Date: 16 September 2016
Date Type: Publication
Series Name: CEUR Workshop Proceedings
Journal or Publication Title: Proceedings of Joint Workshop on Interfaces and Human Decision Making for Recommender Systems at 10th ACM Conference on Recommender Systems
Volume: 1679
Publisher: CEUR
Page Range: pp. 28-35
Event Title: Joint Workshop on Interfaces and Human Decision Making for Recommender Systems at 10th ACM Conference on Recommender Systems
Event Dates: 16 Sep 2016
Event Type: Workshop
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
Uncontrolled Keywords: recommender interface adaptive-visualization
ISSN: 1613-0073
Official URL: http://ceur-ws.org/Vol-1679/paper5.pdf
Date Deposited: 09 Aug 2017 15:15
Last Modified: 09 Aug 2017 15:15
URI: http://d-scholarship.pitt.edu/id/eprint/32808

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