2022 International Conference on Innovations in Science, Engineering and Technology (ICISET) 2022
DOI: 10.1109/iciset54810.2022.9775913
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Bengali Text Categorization Based on Deep Hybrid CNN–LSTM Network with Word Embedding

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Cited by 8 publications
(1 citation statement)
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“…In the research work [25], the authors have taken data from open resources which are containing the Bangla newspaper article corpus with 12 categories. For categorizing these article datasets, they have used word embedding methods to extract features from raw data and then used deep learning methods: Convolutional Neural Network (CNN), Artificial Neural Network (ANN), Long Short-term memory (LSTM) and Hybrid (CNN+Bi-LSTM) methods to classify them based on their contents.…”
Section: Mandal and Senmentioning
confidence: 99%
“…In the research work [25], the authors have taken data from open resources which are containing the Bangla newspaper article corpus with 12 categories. For categorizing these article datasets, they have used word embedding methods to extract features from raw data and then used deep learning methods: Convolutional Neural Network (CNN), Artificial Neural Network (ANN), Long Short-term memory (LSTM) and Hybrid (CNN+Bi-LSTM) methods to classify them based on their contents.…”
Section: Mandal and Senmentioning
confidence: 99%