Sustainability Evaluation Metrics for Recommender Systems
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866909712256073728 |
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| author | Felfernig, Alexander Garber, Damian Le, Viet-Man Lubos, Sebastian Tran, Thi Ngoc Trang |
| author_facet | Felfernig, Alexander Garber, Damian Le, Viet-Man Lubos, Sebastian Tran, Thi Ngoc Trang |
| contents | Sustainability-oriented evaluation metrics can help to assess the quality of recommender systems beyond wide-spread metrics such as accuracy, precision, recall, and satisfaction. Following the United Nations`s sustainable development goals (SDGs), such metrics can help to analyse the impact of recommender systems on environmental, social, and economic aspects. We discuss different basic sustainability evaluation metrics for recommender systems and analyze their applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_22520 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Sustainability Evaluation Metrics for Recommender Systems Felfernig, Alexander Garber, Damian Le, Viet-Man Lubos, Sebastian Tran, Thi Ngoc Trang Information Retrieval Sustainability-oriented evaluation metrics can help to assess the quality of recommender systems beyond wide-spread metrics such as accuracy, precision, recall, and satisfaction. Following the United Nations`s sustainable development goals (SDGs), such metrics can help to analyse the impact of recommender systems on environmental, social, and economic aspects. We discuss different basic sustainability evaluation metrics for recommender systems and analyze their applications. |
| title | Sustainability Evaluation Metrics for Recommender Systems |
| topic | Information Retrieval |
| url | https://arxiv.org/abs/2507.22520 |