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Text Analysis for Bengali Text Summarization Using Deep Learning

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dc.contributor.author Munzir, Abdullah Al
dc.contributor.author Rahman, Md. Lutfor
dc.contributor.author Abujar, Sheikh
dc.contributor.author Ohidujjaman
dc.contributor.author Hossain, Syed Akhter
dc.date.accessioned 2021-12-30T04:01:45Z
dc.date.available 2021-12-30T04:01:45Z
dc.date.issued 2019-12-30
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6599
dc.description.abstract Text summarization is an approach by which the size of one or more document is shortened and the shorten passage presents the core information of the document. In this modern era of information technology, we are over flooded with online data which raised the necessity of summary of the original text. Many methods have already implemented for English text and the effort for Bengali text are gaining alongside. In this paper, we propose an extractive text summarization technique based on a deep learning model of Recurrent Neural Network (RNN) for single document summary. Our method is to classify the sentences as significant or not for the summary. We have used Long Short-Term Memory (LSTM), Gated Recurrent Units (GRU) based RNN. Between them, we found LSTM more promising and we achieved average F1 scores- 0.63, 0.59, 0.56 for Rouge-1, Rouge-2 and Rouge-3 in some respects. en_US
dc.language.iso en_US en_US
dc.publisher 10th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2019, IEEE en_US
dc.subject Text data mining en_US
dc.subject Text analysis en_US
dc.subject Machine learning en_US
dc.subject Deep learning en_US
dc.title Text Analysis for Bengali Text Summarization Using Deep Learning en_US
dc.type Article en_US


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