Leveraging interfaces to improve recommendation diversity

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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 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, 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). Association for Computing Machinery, Inc. https://doi.org/10.1145/3099023.3099073

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