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GAMMA: A Graph and Multi-view Memory Attention Mechanism for Top-N Heterogeneous Recommendation
Exploiting heterogeneous information networks (HIN) to top-N recommendation has been shown to alleviate the data sparsity problem present in recommendation systems. This requires careful effort in extracting relevant knowledge from HIN. However, existing models in this setting have the following sho...
Autores principales: | Vijaikumar, M., Shevade, Shirish, Narasimha Murty, M. |
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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/PMC7206146/ http://dx.doi.org/10.1007/978-3-030-47426-3_3 |
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