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Beyond the topics: how deep learning can improve the discriminability of probabilistic topic modelling
The article presents a discriminative approach to complement the unsupervised probabilistic nature of topic modelling. The framework transforms the probabilities of the topics per document into class-dependent deep learning models that extract highly discriminatory features suitable for classificati...
Autores principales: | Al Moubayed, Noura, McGough, Stephen, Awwad Shiekh Hasan, Bashar |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7924555/ https://www.ncbi.nlm.nih.gov/pubmed/33816904 http://dx.doi.org/10.7717/peerj-cs.252 |
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