Abstractive Text Summarization for Bangla Language Using NLP and Machine Learning Approaches
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Abstract (arXiv)
Text summarization involves reducing extensive documents to short sentences that encapsulate the essential ideas. The goal is to create a summary that effectively conveys the main points of the original text. We spend a significant amount of time each day reading the newspaper to stay informed about current events both domestically and internationally. While reading newspapers enriches our knowledge, we sometimes come across unnecessary content that isn't particularly relevant to our lives. In this paper, we introduce a neural network model designed to summarize Bangla text into concise and straightforward paragraphs, aiming for greater stability and efficiency.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 9 of its 19 references that are in the map. First posted on arXiv 25 Jan 2025.
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9 of 19 references.
References · 9
- 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,530
- 2014Sequence to Sequence Learning with Neural Networkscited by 2,974
- 2015Teaching Machines to Read and Comprehendcited by 1,039
- 2015Effective Approaches to Attention-based Neural Machine Translationcited by 1,024
- 2015A Neural Attention Model for Abstractive Sentence Summarizationcited by 394
- 2014Grammar as a Foreign Languagecited by 70
- 2024Enhancing Bangla Language Next Word Prediction and Sentence Completion through Extended RNN with Bi-LSTM Model On N-gram Languagecited by 3
- 2024Sentiment Polarity Analysis of Bangla Food Reviews Using Machine and Deep Learning Algorithmscited by 3
- 2024English offensive text detection using CNN based Bi-GRU modelcited by 1
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Citing papers per year: 2025: 1.
1 paper.