Text analysis for Bengali Text Summarization using Deep Learning
| Autor: | Abdullah Al Munzir, Sheikh Abujar, Md. Lutfor Rahman, Syed Akhter Hossain, Ohidujjaman |
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| Rok vydání: | 2019 |
| Předmět: |
business.industry
Computer science Deep learning 05 social sciences Information technology 02 engineering and technology computer.software_genre Automatic summarization language.human_language Recurrent neural network Bengali Text mining 020204 information systems 0502 economics and business Core (graph theory) 0202 electrical engineering electronic engineering information engineering language 050211 marketing Artificial intelligence business computer Natural language processing Document summary |
| Zdroj: | ICCCNT |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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