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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...
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| Yayımlandı: | PeerJ Comput Sci |
|---|---|
| Asıl Yazarlar: | , , |
| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
PeerJ Inc.
2020
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| Konular: | |
| Online Erişim: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7924555/ https://ncbi.nlm.nih.gov/pubmed/33816904 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.7717/peerj-cs.252 |
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