Leveraging interfaces to improve recommendation diversity

Chun Hua Tsai, Peter Brusilovsky

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

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 e.ect that a visual interface can have on this issue. .is 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 pa.ern between ranked list and visual interfaces. .e results show that a visual interface can help the user explore a a more diverse set of recommended items.

Original languageEnglish (US)
Title of host publicationUMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization
PublisherAssociation for Computing Machinery, Inc
Pages65-70
Number of pages6
ISBN (Electronic)9781450350679
DOIs
StatePublished - Jul 9 2017
Event25th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2017 - Bratislava, Slovakia
Duration: Jul 9 2017Jul 12 2017

Publication series

NameUMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization

Conference

Conference25th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2017
CountrySlovakia
CityBratislava
Period7/9/177/12/17

All Science Journal Classification (ASJC) codes

  • Software

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