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<!DOCTYPE html> <html > <head> <meta charset="utf-8"> <meta rel="search" type="application/opensearchdescription+xml" href="/open_search.xml" title="Academia.edu"> <meta content="width=device-width, initial-scale=1" name="viewport"> <meta name="google-site-verification" content="bKJMBZA7E43xhDOopFZkssMMkBRjvYERV-NaN4R6mrs"> <meta name="csrf-param" content="authenticity_token" /> <meta name="csrf-token" content="dvLuVfM3h1ug+0wogty0hQUigb3WaewhbZpUB2gcCG1wMNjY6XbNovmx96I+whE0KJnW5vZXWO259Zn4XDw1Sw==" /> <meta name="citation_title" content="Study of Abstractive Text Summarization Techniques" /> <meta name="citation_author" content="ajer research" /> <meta name="twitter:card" content="summary" /> <meta name="twitter:url" content="https://www.academia.edu/34359180/Study_of_Abstractive_Text_Summarization_Techniques" /> <meta name="twitter:title" content="Study of Abstractive Text Summarization Techniques" /> <meta name="twitter:description" content="Nowadays, people use the internet to find information through information retrieval tools such as Google, Yahoo, Bing and so on. 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So, it is not possible for users to" /> <title>(PDF) Study of Abstractive Text Summarization Techniques | ajer research - Academia.edu</title> <link rel="canonical" href="https://www.academia.edu/34359180/Study_of_Abstractive_Text_Summarization_Techniques" /> <script async src="https://www.googletagmanager.com/gtag/js?id=G-5VKX33P2DS"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-5VKX33P2DS', { cookie_domain: 'academia.edu', send_page_view: false, }); gtag('event', 'page_view', { 'controller': "single_work", 'action': "show", 'controller_action': 'single_work#show', 'logged_in': 'false', 'edge': 'unknown', // Send nil if there is no A/B test bucket, in case some records get logged // with missing data - that way we can distinguish between the two cases. // ab_test_bucket should be of the form <ab_test_name>:<bucket> 'ab_test_bucket': null, }) </script> <script> var $controller_name = 'single_work'; var $action_name = "show"; var $rails_env = 'production'; var $app_rev = '92477ec68c09d28ae4730a4143c926f074776319'; var $domain = 'academia.edu'; var $app_host = "academia.edu"; var $asset_host = "academia-assets.com"; var $start_time = new Date().getTime(); var $recaptcha_key = "6LdxlRMTAAAAADnu_zyLhLg0YF9uACwz78shpjJB"; var $recaptcha_invisible_key = "6Lf3KHUUAAAAACggoMpmGJdQDtiyrjVlvGJ6BbAj"; var $disableClientRecordHit = false; </script> <script> window.require = { config: function() { return function() {} } } </script> <script> window.Aedu = window.Aedu || {}; window.Aedu.hit_data = null; window.Aedu.serverRenderTime = new Date(1732838650000); window.Aedu.timeDifference = new Date().getTime() - 1732838650000; </script> <script type="application/ld+json">{"@context":"https://schema.org","@type":"ScholarlyArticle","abstract":"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 \u0026amp;amp;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.","author":[{"@context":"https://schema.org","@type":"Person","name":"ajer research"}],"contributor":[],"dateCreated":"2017-08-26","dateModified":"2017-08-26","datePublished":null,"headline":"Study of Abstractive Text Summarization Techniques","inLanguage":"en","keywords":["Bioinformatics","Computer Science","Artificial Intelligence","Information Security","Machine Learning","Data Mining","Computational Linguistics","Computational Biology","Computer Security"],"locationCreated":null,"publication":null,"publisher":{"@context":"https://schema.org","@type":"Organization","name":null},"image":null,"thumbnailUrl":null,"url":"https://www.academia.edu/34359180/Study_of_Abstractive_Text_Summarization_Techniques","sourceOrganization":[{"@context":"https://schema.org","@type":"EducationalOrganization","name":null}]}</script><link rel="stylesheet" media="all" 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"https://www.academia.edu/login?post_login_redirect_url=https%3A%2F%2Fwww.academia.edu%2F34359180%2FStudy_of_Abstractive_Text_Summarization_Techniques%3Fauto%3Ddownload"; window.loswp.translateUrl = "https://www.academia.edu/login?post_login_redirect_url=https%3A%2F%2Fwww.academia.edu%2F34359180%2FStudy_of_Abstractive_Text_Summarization_Techniques%3Fshow_translation%3Dtrue"; window.loswp.previewableAttachments = [{"id":54249988,"identifier":"Attachment_54249988","shouldShowBulkDownload":false}]; window.loswp.shouldDetectTimezone = true; window.loswp.shouldShowBulkDownload = true; window.loswp.showSignupCaptcha = false window.loswp.willEdgeCache = false; window.loswp.work = {"work":{"id":34359180,"created_at":"2017-08-26T03:06:22.879-07:00","from_world_paper_id":null,"updated_at":"2021-01-14T11:46:03.714-08:00","_data":{"abstract":"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 \u0026wordnet 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."},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"Study of Abstractive Text Summarization Techniques","broadcastable":true,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [35351999]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "control"; 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 class="ds-work-card--grid-container"><div class="ds-work-card--container js-loswp-work-card"><div class="ds-work-card--cover"><div class="ds-work-cover--wrapper"><div class="ds-work-cover--container"><button class="ds-work-cover--clickable js-swp-download-button" data-signup-modal="{"location":"swp-splash-paper-cover","attachmentId":54249988,"attachmentType":"pdf"}"><img alt="First page of “Study of Abstractive Text Summarization Techniques”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/54249988/mini_magick20190117-9705-1wwgd79.png?1547777063" /><img alt="PDF Icon" class="ds-work-cover--file-icon" src="//a.academia-assets.com/assets/single_work_splash/adobe.icon-574afd46eb6b03a77a153a647fb47e30546f9215c0ee6a25df597a779717f9ef.svg" /><div class="ds-work-cover--hover-container"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span><p>Download Free PDF</p></div><div 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">Study of Abstractive Text Summarization 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="35351999" href="https://independent.academia.edu/ajerresearch"><img alt="Profile image of ajer research" class="ds-work-card--author-avatar" src="//a.academia-assets.com/images/s65_no_pic.png" />ajer research</a></div><div class="ds-work-card--detail"><div class="ds-work-card--work-metadata"><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">visibility</span><p class="ds2-5-body-sm" id="work-metadata-view-count">…</p></div><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">description</span><p class="ds2-5-body-sm">8 pages</p></div><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">link</span><p class="ds2-5-body-sm">1 file</p></div></div><script>(async () => { const workId = 34359180; const worksViewsPath = "/v0/works/views?subdomain_param=api&work_ids%5B%5D=34359180"; const getWorkViews = async (workId) => { const response = await fetch(worksViewsPath); if (!response.ok) { throw new Error('Failed to load work views'); } const data = await response.json(); return data.views[workId]; }; // Get the view count for the work - we send this immediately rather than waiting for // the DOM to load, so it can be available as soon as possible (but without holding up // the backend or other resource requests, because it's a bit expensive and not critical). const viewCount = await getWorkViews(workId); const updateViewCount = (viewCount) => { const viewCountNumber = Number(viewCount); if (!viewCountNumber) { throw new Error('Failed to parse view count'); } const commaizedViewCount = viewCountNumber.toLocaleString(); const viewCountBody = document.getElementById('work-metadata-view-count'); if (viewCountBody) { viewCountBody.textContent = `${commaizedViewCount} views`; } else { throw new Error('Failed to find work views element'); } }; // If the DOM is still loading, wait for it to be ready before updating the view count. if (document.readyState === "loading") { document.addEventListener('DOMContentLoaded', () => { updateViewCount(viewCount); }); // Otherwise, just update it immediately. } else { updateViewCount(viewCount); } })();</script></div><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">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-work-card--button-container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--work-card","attachmentId":54249988,"attachmentType":"pdf","workUrl":"https://www.academia.edu/34359180/Study_of_Abstractive_Text_Summarization_Techniques"}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--work-card","attachmentId":54249988,"attachmentType":"pdf","workUrl":"https://www.academia.edu/34359180/Study_of_Abstractive_Text_Summarization_Techniques"}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div></div><div data-auto_select="false" data-client_id="331998490334-rsn3chp12mbkiqhl6e7lu2q0mlbu0f1b" data-doc_id="54249988" data-landing_url="https://www.academia.edu/34359180/Study_of_Abstractive_Text_Summarization_Techniques" data-login_uri="https://www.academia.edu/registrations/google_one_tap" data-moment_callback="onGoogleOneTapEvent" 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="82447179" 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/82447179/A_Comparative_Study_on_Various_Approaches_and_Complexities_of_Text_Summarization">A Comparative Study on Various Approaches and Complexities 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="116336976" href="https://msrit.academia.edu/PramodaDevi">Pramoda Devi</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2020</p><p class="ds-related-work--abstract ds2-5-body-sm">In today’s digitalized world web is having at most information for users, additional to that newspaper, textbook and magazine are offline resource of information. Web consist of million and billions of resources in the form of documentsin additional to that many documents in different domain are adding to it, thus data is growing exponentially. To understand and assimilate this data many applications of natural language processing came to existence namely, Text mining, Information Retrieval, Machine Translation, Question and answering, text summarization and many more. Research on text summarization started over seven decades and till now effective method or system is not available to generate summary as human. In this paper, surveys the recent literature on different automatic text summarization method and propose idea of abstractive text summarization form orphologically rich language, kannada which is still lacking in field of text summarization.</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 Comparative Study on Various Approaches and Complexities of Text Summarization","attachmentId":88154772,"attachmentType":"pdf","work_url":"https://www.academia.edu/82447179/A_Comparative_Study_on_Various_Approaches_and_Complexities_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/82447179/A_Comparative_Study_on_Various_Approaches_and_Complexities_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="1" data-entity-id="40914991" 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/40914991/Survey_on_Abstractive_Text_Summarization_using_various_approaches">Survey on Abstractive Text Summarization using various approaches</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="59921007" href="https://vit-in.academia.edu/Chitturiarunkrishna">Arun Krishna Chitturi</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal of Advanced Trends in Computer Science and Engineering, 2019</p><p class="ds-related-work--abstract ds2-5-body-sm">Text summarization is the core aspects of Natural Language processing. Summarized text should consist of unique sentences. It is used in many situations in today's Information technological word, one of the best examples is in understanding customer feedbacks in companies. This job can be done by humans, but if the text or data that has to be summarized then it will consume lot of time and work force. This situation lead to birth of different approaches in summarization. This paper addresses and concentrates on various methods and approaches and their results in abstractive text summarization. This survey gives an insight about different types of text summarization and various methods used in abstractive text summarization in recent developments.</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 Abstractive Text Summarization using various approaches","attachmentId":61647195,"attachmentType":"pdf","work_url":"https://www.academia.edu/40914991/Survey_on_Abstractive_Text_Summarization_using_various_approaches","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/40914991/Survey_on_Abstractive_Text_Summarization_using_various_approaches"><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="33775488" 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/33775488/A_Comprehensive_Survey_on_Extractive_Text_Summarization_Techniques">A Comprehensive Survey on Extractive 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">ABSTRACT: Automated data collection tools and matured database technology lead to tremendous amounts of data stored in database, data warehouses and other data repositories. With the increasing amount of online information, it becomes extremely difficult to find relevant information to users. Information retrieval system usually returns a large amount of documents listed in the order of estimated relevance. It is not possible for users to read each document in order to find the useful one. Automatic text summarization system, one of the special data mining applications, helps in this task by providing a quick summary of the information contained in the document(s). Some efficient work has been done for text summarization on various languages. But among them there are a few works on Bengali language. It has thus motivated us to do develop or modify a new or existing summarization technique for Bengali document(s) and to provide us an opportunity to make some contribution in natural language processing. To do the same, we have surveyed and compared some techniques on extractive text summarization on various languages in this paper. The summarizations have done for single or multiple documents in different languages. Finally, a comparative nomenclature on the discussed single or multi-document summarization techniques has been conducted.</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 Comprehensive Survey on Extractive Text Summarization Techniques","attachmentId":53763698,"attachmentType":"pdf","work_url":"https://www.academia.edu/33775488/A_Comprehensive_Survey_on_Extractive_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/33775488/A_Comprehensive_Survey_on_Extractive_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="3" data-entity-id="89968429" 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/89968429/Automatic_Text_Summarization_for_Bengali_Language_Including_Grammatical_Analysis">Automatic Text Summarization for Bengali Language Including Grammatical Analysis</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="105976214" href="https://bsmrstu.academia.edu/RSikder">Ratul Sikder</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal of Scientific & Technology Research, 2019</p><p class="ds-related-work--abstract ds2-5-body-sm">Text summarization is a process of summarize any text or document. There are many summarization tools for English language. There are also a few works for automated Bengali text or document summarization. The tools are seemed not much appropriate from application point of view. Summarization is categorized in two ways: extractive and abstractive approach. Most of the summarizer methods for Bengali text summarization are extractive. Those proposed methods can‘t extract whole theme of a text document. Reader can be satisfied about summary if it gives full important information of input document. Our proposed method introduces an enhanced summarization method that can improved the quality of outputs. The proposed method is modeled combining a set mathematical rules and Bengali grammatical rules. This method also solves many problems of extractive summarizer and it also introduces the path of abstractive summarization methods. Although the method has been developed for Bengali language,...</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":"Automatic Text Summarization for Bengali Language Including Grammatical Analysis","attachmentId":93661865,"attachmentType":"pdf","work_url":"https://www.academia.edu/89968429/Automatic_Text_Summarization_for_Bengali_Language_Including_Grammatical_Analysis","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/89968429/Automatic_Text_Summarization_for_Bengali_Language_Including_Grammatical_Analysis"><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="4" data-entity-id="44084511" 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/44084511/IJERT_Text_Summarizer_Using_Abstractive_and_Extractive_Method">IJERT-Text Summarizer Using Abstractive and Extractive Method</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="109571315" href="https://independent.academia.edu/IJERTORG">IJERT Journal</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal of Engineering Research and Technology (IJERT), 2014</p><p class="ds-related-work--abstract ds2-5-body-sm">https://www.ijert.org/text-summarizer-using-abstractive-and-extractive-method https://www.ijert.org/research/text-summarizer-using-abstractive-and-extractive-method-IJERTV3IS050821.pdf the challenge of how to make computer understand the document with any extension and how to make it generate the summary is the main motivation. Reducing the time and effort of the user of reading through entire document to know what the document is about is also the driving force behind this work. To summarize large documents of the text will be difficult for human beings. Extractive and abstractive summarization is two types of summarization. An extractive summarization method is concatenating important sentences or paragraphs without understanding the meaning of those sentences. An abstractive summarization method is generating the meaningful summary. The system uses is a culmination of both statistical and linguistic analysis of text document. Summary generated is better than mere statistical summarizers that generate summary based on word frequency calculation. Addition of plural resolution and abbreviation resolution adds more precision to summary. Concept of normalization introduced here makes sentences get their weights purely based on value of its content words and not on number of words it has. Therefore even a small but important sentence gets its place based on values of words it has. Adding linguistic features to the algorithm fine tunes the summary to higher level.</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":"IJERT-Text Summarizer Using Abstractive and Extractive Method","attachmentId":64429734,"attachmentType":"pdf","work_url":"https://www.academia.edu/44084511/IJERT_Text_Summarizer_Using_Abstractive_and_Extractive_Method","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/44084511/IJERT_Text_Summarizer_Using_Abstractive_and_Extractive_Method"><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="5" data-entity-id="12783813" 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/12783813/A_REVIEW_PAPER_ON_TEXT_SUMMARIZATION_OF_HINDI_DOCUMENTS">A REVIEW PAPER ON TEXT SUMMARIZATION OF HINDI DOCUMENTS</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="3448233" href="https://independent.academia.edu/IJRCARJOURNAL">IJRCAR JOURNAL</a></div><p class="ds-related-work--metadata ds2-5-body-xs">IJRCAR, 2015</p><p class="ds-related-work--abstract ds2-5-body-sm">A summary of a document is a (much) shorter text conveys the most important information from the source document. Summary of the text must contain important information from the document. Summary of the text can be generated from a single document or from multiple documents. In single-document summarization, the summary of only one document is to be built, while in multi-document summarization the summary of a whole collection of documents (such as all today’s news or all search results for a query) is built. In this paper authors have represented review on single-document summaries for the text data written in the various Languages. This paper also presents detection and removal of Deadwood, Extractive and Abstractive summarization methods for Punjabi language. An Extractive summarization method only decides, for each sentence, whether or not it will be included in the summary. An Abstractive summarization process consists of “understanding” the original text and “re-telling” it in fewer words</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 REVIEW PAPER ON TEXT SUMMARIZATION OF HINDI DOCUMENTS","attachmentId":37819177,"attachmentType":"pdf","work_url":"https://www.academia.edu/12783813/A_REVIEW_PAPER_ON_TEXT_SUMMARIZATION_OF_HINDI_DOCUMENTS","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/12783813/A_REVIEW_PAPER_ON_TEXT_SUMMARIZATION_OF_HINDI_DOCUMENTS"><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="6" data-entity-id="97595340" 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/97595340/An_Extractive_Text_Summarization_Technique_for_Bengali_Document_s_using_K_means_Clustering_Algorithm">An Extractive Text Summarization Technique for Bengali Document(s) using K-means Clustering Algorithm</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="130133202" href="https://rkict.academia.edu/SumaiyaAkter">Sumya Akter</a></div><p class="ds-related-work--metadata ds2-5-body-xs">IcIVPR, 2017</p><p class="ds-related-work--abstract ds2-5-body-sm">Text summarization, a field of data mining, is very important for developing various real-life applications. Many techniques have been developed for summarizing English text(s). But, a few attempts have been made for Bengali text because of its some multifaceted structure. This paper presents a method for text summarization which extracts important sentences from a single or multiple Bengali documents. The input document(s) should be pre-processed by tokenization, stemming operation etc. Then, word score is calculated by Term-Frequency/Inverse Document Frequency (TF/IDF) and sentence score is determined by summing up its constituent words' scores with its position. Cue and skeleton words have also been considered to calculate the sentence score. For single or multiple documents, K-means clustering algorithm has been applied to produce the final summary. The experimental result shows satisfactory outputs in comparison to the existing approaches possessing linear run time complexity.</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 Extractive Text Summarization Technique for Bengali Document(s) using K-means Clustering Algorithm","attachmentId":99174449,"attachmentType":"pdf","work_url":"https://www.academia.edu/97595340/An_Extractive_Text_Summarization_Technique_for_Bengali_Document_s_using_K_means_Clustering_Algorithm","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/97595340/An_Extractive_Text_Summarization_Technique_for_Bengali_Document_s_using_K_means_Clustering_Algorithm"><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="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="8" data-entity-id="8821589" 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/8821589/Automatic_Summarization_of_Text_Documents_Written_in_Hindi_Language">Automatic Summarization of Text Documents Written in Hindi Language</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="2902340" href="https://ijcsmc.academia.edu/IJCSMCJournal">IJCSMC Journal</a></div><p class="ds-related-work--abstract ds2-5-body-sm">A summary of a document is a shorter text conveys the most important information from the source document. Summary of the text must contain important information from the document. Summary of the text can be generated from a single document or from multiple documents. In single-document summarization the summary of only one document is to be built while in multi-document summarization the summary of a whole collection of documents (such as all today’s news or all search results for a query) is built. In this paper have represented on single-document summaries for the text data written in the Hindi (Devanagri Script). Language contains history information. This paper also presents detection and removal of Deadwood, Extractive and Abstractive summarization methods designed for Hindi language such document contains history information. An Extractive summarization method only decides, for each sentence, whether or not it will be included in the summary. An Abstractive summarization process consists of “understanding” the original text and “re-telling” it in fewer words.</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":"Automatic Summarization of Text Documents Written in Hindi Language","attachmentId":35165137,"attachmentType":"pdf","work_url":"https://www.academia.edu/8821589/Automatic_Summarization_of_Text_Documents_Written_in_Hindi_Language","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/8821589/Automatic_Summarization_of_Text_Documents_Written_in_Hindi_Language"><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="56756084" 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/56756084/A_Survey_of_Automatic_Text_Summarization_System_for_Different_Regional_Language_in_India">A Survey of Automatic Text Summarization System for Different Regional Language in India</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="49552756" href="https://independent.academia.edu/SSDGCTsPrincipal">SSDGCT's Principal</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Bonfring International Journal of Software Engineering and Soft Computing</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 of Automatic Text Summarization System for Different Regional Language in India","attachmentId":71984253,"attachmentType":"pdf","work_url":"https://www.academia.edu/56756084/A_Survey_of_Automatic_Text_Summarization_System_for_Different_Regional_Language_in_India","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/56756084/A_Survey_of_Automatic_Text_Summarization_System_for_Different_Regional_Language_in_India"><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":54249988,"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":54249988,"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_54249988" 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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