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It is very difficult for human beings to manually summarize large documents of text. Text Summarization methods can be classified into extractive and abstractive summarization. An extractive summarization method consists of selecting important sentences, paragraphs etc. from the original document and concatenating them into shorter form. The importance of sentences is decided based on statistical and linguistic features of sentences. An abstractive summarization method consists of understanding the original text and re-telling it in fewer words. It uses linguistic methods to examine and interpret the text and then to find the new concepts and expressions to best describe it by generating a new shorter text that conveys the most important information from the original text document. In this paper, a Survey of Text Summarization Extractive techniques has been presented.","publication_date":"2010,,","publication_name":"Journal of Emerging Technologies in Web Intelligence","grobid_abstract_attachment_id":"94757319"},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"A Survey of Text Summarization Extractive Techniques","broadcastable":true,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [31330638]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "full_page_mobile_sutd_modal"; window.loswp.useOptimizedScribd4genScript = false; window.loswp.appleClientId = 'edu.academia.applesignon';</script><script defer="" src="https://accounts.google.com/gsi/client"></script><div class="ds-loswp-container"><div 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class="ds-work-cover--ribbon-container">Download Free PDF</div><div class="ds-work-cover--ribbon-triangle"></div></button></div></div></div><div class="ds-work-card--work-information"><h1 class="ds-work-card--work-title">A Survey of Text Summarization Extractive Techniques</h1><div class="ds-work-card--work-authors ds-work-card--detail"><a class="ds-work-card--author js-wsj-grid-card-author ds2-5-body-md ds2-5-body-link" data-author-id="31330638" href="https://punjabiuniversity.academia.edu/GurpreetSinghLehal"><img alt="Profile image of Gurpreet Singh Lehal" class="ds-work-card--author-avatar" src="//a.academia-assets.com/images/s65_no_pic.png" />Gurpreet Singh Lehal</a></div><div class="ds-work-card--detail"><p class="ds-work-card--detail ds2-5-body-sm">2010, Journal of Emerging Technologies in Web Intelligence</p></div><div class="ds-work-card--button-container"><button class="ds2-5-button js-swp-download-button" 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id="g_id_onload"></div><div class="ds-top-related-works--grid-container"><div class="ds-related-content--container ds-top-related-works--container"><h2 class="ds-related-content--heading">Related papers</h2><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="0" data-entity-id="53209721" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/53209721/Comparative_Study_of_Text_Summarization_Methods">Comparative Study of Text Summarization Methods</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="6742617" href="https://mu.academia.edu/NikitaMunot">Nikita Munot</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal of Computer Applications, 2014</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Comparative Study of Text Summarization Methods","attachmentId":70105940,"attachmentType":"pdf","work_url":"https://www.academia.edu/53209721/Comparative_Study_of_Text_Summarization_Methods","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/53209721/Comparative_Study_of_Text_Summarization_Methods"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="1" data-entity-id="36206292" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/36206292/SURVEY_ON_TEXT_SUMMARIZATION_METHODS">SURVEY ON TEXT SUMMARIZATION METHODS</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="39122404" href="https://iaeme.academia.edu/publication">IAEME Publication</a></div><p class="ds-related-work--abstract ds2-5-body-sm">Text summarization is the process of shortening the source document into condensed form keeps overall idea about the document. The techniques of text summarization are abstractive and extractive. The abstractive summarization requires natural language processing tools for summarizing the documents. The extractive summarization requires statistical, linguistics and heuristics methods for ranking the sentences. Many techniques have been developed for summarization of text in various languages. This paper discuss about the methods of abstractive and extractive text summarization and its merits and de-merits. The study also shows that the extractive methods are easy to implement and give better result in summarization within short span of time.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"SURVEY ON TEXT SUMMARIZATION METHODS","attachmentId":56107626,"attachmentType":"pdf","work_url":"https://www.academia.edu/36206292/SURVEY_ON_TEXT_SUMMARIZATION_METHODS","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/36206292/SURVEY_ON_TEXT_SUMMARIZATION_METHODS"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="36678974" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/36678974/A_Comparative_Study_on_Text_Summarization_Methods">A Comparative Study on Text Summarization Methods</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="26204613" href="https://annauniv.academia.edu/IJETJOURNAL">International Research Group - IJET JOURNAL</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Comparative Study on Text Summarization Methods","attachmentId":56616198,"attachmentType":"pdf","work_url":"https://www.academia.edu/36678974/A_Comparative_Study_on_Text_Summarization_Methods","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/36678974/A_Comparative_Study_on_Text_Summarization_Methods"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="84008292" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/84008292/Analysis_on_Text_Summarization">Analysis on Text Summarization</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="6079060" href="https://independent.academia.edu/IJRASETPublication">IJRASET Publication</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022</p><p class="ds-related-work--abstract ds2-5-body-sm">As we enter the 21st century, with the advent of mobile phones and access to information stores, we seem to be surrounded by more information, less time, or the ability to process it. 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ds2-5-body-xs">International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2022</p><p class="ds-related-work--abstract ds2-5-body-sm">There have been considerable advancements in Text Summarization over the last few years. There are two ways to text summarization: one is based on natural language processing (NLP), and the other is based on deep learning. In the realm of NLP, text summarization is the most intriguing and challenging task. NLP stands for Natural Language Processing, which studies and manipulates human language by computers. Because of the massive increase in information and data, it has become critical. Text summarization is creating a thorough and meaningful summary of text from various sources such as books, news stories, research papers, and tweets, among others. Large text documents that are difficult to summarize manually are the research subject. The job of condensing a piece of text into a shorter version, minimizing the size of the original text while maintaining key informative components and content meaning, is known as summarising. Because human text summarising is a time-consuming and intrinsically tiresome process, automating it is gaining popularity and hence acts as a potent stimulus for academic study.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Text Summarization using Extractive and Abstractive Techniques","attachmentId":88411426,"attachmentType":"pdf","work_url":"https://www.academia.edu/82836297/Text_Summarization_using_Extractive_and_Abstractive_Techniques","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/82836297/Text_Summarization_using_Extractive_and_Abstractive_Techniques"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="98309079" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/98309079/A_Survey_on_Methods_of_Text_Summarization">A Survey on Methods of Text Summarization</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="14746321" href="https://independent.academia.edu/AshishChakraverti">Ashish Chakraverti</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Zenodo (CERN European Organization for Nuclear Research), 2022</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Survey on Methods of Text Summarization","attachmentId":99695762,"attachmentType":"pdf","work_url":"https://www.academia.edu/98309079/A_Survey_on_Methods_of_Text_Summarization","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/98309079/A_Survey_on_Methods_of_Text_Summarization"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="34359180" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/34359180/Study_of_Abstractive_Text_Summarization_Techniques">Study of Abstractive Text Summarization Techniques</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="35351999" href="https://independent.academia.edu/ajerresearch">ajer research</a></div><p class="ds-related-work--abstract ds2-5-body-sm">Nowadays, people use the internet to find information through information retrieval tools such as Google, Yahoo, Bing and so on. Because of the increasing rate of data, people need to get meaningful information. So, it is not possible for users to read each document in order to find the useful one. Among all the modern technologies, text summarization has become an important and timely tool for the users to quickly understand the large volume of information. Automatic text summarization system, one of the special data mining applications that helps this task by providing a quick summary of the information contained in the documents. Text summarization approach is broadly classified into two categories: extractive and abstractive. Many techniques on abstractive text summarization have been developed forthe languages like English, Arabic, Hindi etc. But there is no remarkable abstractive method for Bengali text because individual word of every sentence accesses domain ontology &wordnet and it must require the complete knowledge about each Bengali word, which is lengthy process for summarization. It has thus motivated the authors to observe, analyze and compare the existing techniques so that abstractive summarization technique for Bengali texts can be proposed. To do so, the authors have conducted a survey on abstractive text summarization techniques on various languages in this paper. Finally, a comparative scenario on the discussed single or multi-document summarization techniques has been presented.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Study of Abstractive Text Summarization Techniques","attachmentId":54249988,"attachmentType":"pdf","work_url":"https://www.academia.edu/34359180/Study_of_Abstractive_Text_Summarization_Techniques","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/34359180/Study_of_Abstractive_Text_Summarization_Techniques"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="9" data-entity-id="66066102" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/66066102/An_Overview_of_Text_Summarization">An Overview of Text Summarization</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="51805734" href="https://independent.academia.edu/LaxmiRananavare">Laxmi Rananavare</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal of Computer Applications, 2017</p><p class="ds-related-work--abstract ds2-5-body-sm">The amount of e-information available has increased greatly over the past few decades. As the vast amount of information is available for every theme on Internet, shortening the information in the form of summary would immensely benefit readers. Hence, the natural language processing research community is developing new methods for summarizing the text mechanically. Automatic text summarization system produces a summary, i.e. short length text that includes all the significant information for the article. This paper presents a comprehensive survey of contemporary text summarization of extractive and abstractive approaches.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"An Overview of Text Summarization","attachmentId":77403930,"attachmentType":"pdf","work_url":"https://www.academia.edu/66066102/An_Overview_of_Text_Summarization","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/66066102/An_Overview_of_Text_Summarization"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div></div></div><div class="ds-sticky-ctas--wrapper js-loswp-sticky-ctas hidden"><div class="ds-sticky-ctas--grid-container"><div class="ds-sticky-ctas--container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--sticky-ctas","attachmentId":94757319,"attachmentType":"pdf","workUrl":null}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--sticky-ctas","attachmentId":94757319,"attachmentType":"pdf","workUrl":null}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div><div class="ds-below-fold--grid-container"><div class="ds-work--container js-loswp-embedded-document"><div class="attachment_preview" data-attachment="Attachment_94757319" style="display: none"><div class="js-scribd-document-container"><div class="scribd--document-loading js-scribd-document-loader" style="display: block;"><img alt="Loading..." src="//a.academia-assets.com/images/loaders/paper-load.gif" /><p>Loading Preview</p></div></div><div style="text-align: center;"><div class="scribd--no-preview-alert js-preview-unavailable"><p>Sorry, preview is currently unavailable. 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