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              <text>Extractive Text Summarization Using Sentence Ranking</text>
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              <text>abstractive text summarization; Automatic text summarization; extractive summarization; sentence extraction; term weight</text>
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              <text>Automatic Text summarization is the technique to identify the most useful and necessary information in a text. It has two approaches 1)Abstractive text summarization and 2)Extractive text summarization. An extractive text summarization means an important information or sentence are extracted from the given text file or original document. In this paper, a novel statistical method to perform an extractive text summarization on single document is demonstrated. The method extraction of sentences, which gives the idea of the input text in a short form, is presented. Sentences are ranked by assigning weights and they are ranked based on their weights. Highly ranked sentences are extracted from the input document so it extracts important sentences which directs to a high-quality summary of the input document and store summary as audio.  2019 IEEE.</text>
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              <text>Madhuri J.N.; Ganesh Kumar R.</text>
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              <text>2019 International Conference on Data Science and Communication, IconDSC 2019</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>&lt;a href="https://doi.org/10.1109/IconDSC.2019.8817040" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/IconDSC.2019.8817040&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072766280&amp;amp;doi=10.1109%2FIconDSC.2019.8817040&amp;amp;partnerID=40&amp;amp;md5=3f20c742f944f976c8cd964afb33f4f0" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072766280&amp;amp;doi=10.1109%2fIconDSC.2019.8817040&amp;amp;partnerID=40&amp;amp;md5=3f20c742f944f976c8cd964afb33f4f0&lt;/a&gt;</text>
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              <text>Restricted Access</text>
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              <text>ISBN: 978-153869319-3</text>
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              <text>Madhuri J.N., Dept. of Computer science and Engineering, CHRIST, Deemed to be University, Bangalore, India; Ganesh Kumar R., Dept. of Computer science and Engineering, CHRIST, Deemed to be University, Bangalore, India</text>
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