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A Deep Learning Approach for Bengali Text Summarization

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dc.contributor.author Sorker, Amit Kumer
dc.date.accessioned 2020-12-28T07:45:08Z
dc.date.available 2020-12-28T07:45:08Z
dc.date.issued 2020-07-09
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/5453
dc.description.abstract Anyone can depict his state of mind with the assistance of content. Thusly understanding the significance of the content is significant. In some cases, it is difficult to comprehend the significance of those writings, close by this is additionally tedious. The machine is the most ideal approach to take care of this issue. As a piece of AI, the content outline is an enormous field of research in characteristic language preparing. Assemble programmed content summarizer is the principle centring purpose of all examination. Content summarizer produces an essential part of an enormous report in a brief timeframe. Programmed content summarizer for different dialects has made already however not for the Bengali language. Expanding the devices and innovation of Bengali language is the fundamental objective of this exploration. In this exploration work, I have attempted to fabricate a programmed book summarizer for the Bengali language. However, working with the Bengali language was an extremely testing piece of this examination. Yet, until the end, I have made a base for programmed content summarizer for the Bengali language. The dataset utilized is gathered from an online web-based life. The profound learning model is utilized to make the summarizer. In the model, train time lessen the misfortune is legitimately influence the investigation result. I have diminished the preparation loss of our rundown model for Bengali content summarizer and which are competent to create a short book outline. en_US
dc.language.iso en en_US
dc.publisher Daffodil International University en_US
dc.subject Learning System en_US
dc.subject Programming Language en_US
dc.title A Deep Learning Approach for Bengali Text Summarization en_US
dc.type Other en_US


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