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International Workshop on Algorithmic Bias in Search and Recommendation (Bias 2020)
Both search and recommendation algorithms provide results based on their relevance for the current user. In order to do so, such a relevance is usually computed by models trained on historical data, which is biased in most cases. Hence, the results produced by these algorithms naturally propagate, a...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7148070/ http://dx.doi.org/10.1007/978-3-030-45442-5_84 |