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A List-Ranking Framework Based on Linear and Non-Linear Fusion for Recommendation from Implicit Feedback
Although most list-ranking frameworks are based on multilayer perceptrons (MLP), they still face limitations within the method itself in the field of recommender systems in two respects: (1) MLP suffer from overfitting when dealing with sparse vectors. At the same time, the model itself tends to lea...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9222433/ https://www.ncbi.nlm.nih.gov/pubmed/35741499 http://dx.doi.org/10.3390/e24060778 |