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A sampling approach to Debiasing the offline evaluation of recommender systems
Offline evaluation of recommender systems (RSs) mostly relies on historical data, which is often biased. The bias is a result of many confounders that affect the data collection process. In such biased data, user-item interactions are Missing Not At Random (MNAR). Measures of recommender system perf...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9001624/ https://www.ncbi.nlm.nih.gov/pubmed/35493700 http://dx.doi.org/10.1007/s10844-021-00651-y |