Being Diverse is Not Enough: Rethinking Diversity Evaluation to Meet Challenges of News Recommender Systems-Reference-Cited by-同舟云学术

Being Diverse is Not Enough: Rethinking Diversity Evaluation to Meet Challenges of News Recommender Systems

Published:2022-07-04 Issue: Volume: Page:
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Container-title:Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization
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Author:

Treuillier Celina¹,Castagnos Sylvain¹,Dufraisse Evan²,Brun Armelle¹

Affiliation:

1. Universite de Lorraine - CNRS - LORIA - BIRD Team, France

2. CEA - LIST, France

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3511047.3538030

Reference91 articles.

1. On over-specialization and concentration bias of recommendations

2. On Unexpectedness in Recommender Systems: Or How to Better Expect the Unexpected;Adamopoulos Panagiotis;ACM Trans. Intell. Syst. Technol.,2014

3. Gediminas Adomavicius and YoungOk Kwon . 2011 . Maximizing Aggregate Recommendation Diversity: A Graph-Theoretic Approach. In Workshop on Novelty and Diversity in Recommender Systems (DiveRS 2011), held in conjunction with ACM RecSys’11. ACM, Chicago, USA, 3–10. Gediminas Adomavicius and YoungOk Kwon. 2011. Maximizing Aggregate Recommendation Diversity: A Graph-Theoretic Approach. In Workshop on Novelty and Diversity in Recommender Systems (DiveRS 2011), held in conjunction with ACM RecSys’11. ACM, Chicago, USA, 3–10.

4. Charu C. Aggarwal . 2016. Recommender Systems - The Textbook . Springer , Berlin, Germany . 1–498 pages. Charu C. Aggarwal. 2016. Recommender Systems - The Textbook. Springer, Berlin, Germany. 1–498 pages.

5. The Welfare Effects of Social Media

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