Leveraging interfaces to improve recommendation diversity

Chun Hua Tsai, Peter Brusilovsky

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

6 Citations (Scopus)

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

Fingerprint

Recommender systems
Visualization

All Science Journal Classification (ASJC) codes

  • Software

Cite this

Tsai, C. H., & Brusilovsky, P. (2017). Leveraging interfaces to improve recommendation diversity. In UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization (pp. 65-70). (UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization). Association for Computing Machinery, Inc. https://doi.org/10.1145/3099023.3099073
Tsai, Chun Hua ; Brusilovsky, Peter. / Leveraging interfaces to improve recommendation diversity. UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery, Inc, 2017. pp. 65-70 (UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization).
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title = "Leveraging interfaces to improve recommendation diversity",
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.",
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Tsai, CH & Brusilovsky, P 2017, Leveraging interfaces to improve recommendation diversity. in UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization. UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization, Association for Computing Machinery, Inc, pp. 65-70, 25th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2017, Bratislava, Slovakia, 7/9/17. https://doi.org/10.1145/3099023.3099073

Leveraging interfaces to improve recommendation diversity. / Tsai, Chun Hua; Brusilovsky, Peter.

UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery, Inc, 2017. p. 65-70 (UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization).

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

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AB - 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.

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Tsai CH, Brusilovsky P. Leveraging interfaces to improve recommendation diversity. In UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery, Inc. 2017. p. 65-70. (UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization). https://doi.org/10.1145/3099023.3099073