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A hybrid approach of Weighted Fine-Tuned BERT extraction with deep Siamese Bi – LSTM model for semantic text similarity identification
The conventional semantic text-similarity methods requires high amount of trained labeled data and also human interventions. Generally, it neglects the contextual-information and word-orders information resulted in data sparseness problem and latitudinal-explosion issue. Recently, deep-learning meth...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Springer US
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8735740/ https://www.ncbi.nlm.nih.gov/pubmed/35018132 http://dx.doi.org/10.1007/s11042-021-11771-6 |