New approaches for evaluation: correctness and freshness: Extended Abstract
Article No.: 14, Pages 1 - 2
Abstract
The main goal of a Recommender System is to suggest relevant items to users, although other utility dimensions -- such as diversity, novelty, confidence, possibility of providing explanations -- are often considered. In this work, we study two dimensions that have been neglected so far in the literature: coverage and temporal novelty. On the one hand, we present a family of metrics that combine precision and coverage in a principled manner (correctness); on the other hand, we provide a measure to account for how much a system is promoting fresh items in its recommendations (freshness). Empirical results show the usefulness of these new metrics to capture more nuances of the recommendation quality.
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Asela Gunawardana and Guy Shani. 2015. Evaluating Recommender Systems. In Recommender Systems Handbook. Springer, 265--308.
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- New approaches for evaluation: correctness and freshness: Extended Abstract
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Published In
June 2018
91 pages
ISBN:9781450365437
DOI:10.1145/3230599
- Conference Chair:
- Jesús Tramullas,
- Program Chairs:
- Raquel Trillo-Lado,
- Javier Nogueras-Iso
Copyright © 2018 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 26 June 2018
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- Short-paper
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- Refereed limited
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- MINECO
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CERI '18
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CERI '18 Paper Acceptance Rate 18 of 24 submissions, 75%;
Overall Acceptance Rate 36 of 51 submissions, 71%
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