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window.loswp.shouldShowBulkDownload = true; window.loswp.showSignupCaptcha = false window.loswp.willEdgeCache = false; window.loswp.work = {"work":{"id":49252725,"created_at":"2021-06-15T10:14:53.892-07:00","from_world_paper_id":null,"updated_at":"2021-06-15T22:16:34.941-07:00","_data":{"abstract":"Computer-implemented systems and methods are described herein for automatically generating questions from text. Text including one or more sentences is received. A sentence, comprising a predicate and one or more arguments associated with the predicate, is parsed from the text. Semantic role labels are assigned to the one or more arguments associated with the predicate. One or more questions are automatically generated relating to the predicate based on the assigned semantic role labels. Each answer to the generated questions is one of the one or more arguments associated with the predicate. ","publication_date":"2021,,","publication_name":"USPTO"},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"Systems and methods for automatic generation of questions from text.","broadcastable":true,"draft":false,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [3199073]; 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":67636432,"attachmentType":"pdf"}"><img alt="First page of “Systems and methods for automatic generation of questions from text.”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/67636432/mini_magick20210615-10078-lker7t.png?1623777326" /><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">Systems and methods for automatic generation of questions from text.</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="3199073" href="https://ets.academia.edu/MichaelFlor"><img alt="Profile image of Michael Flor" class="ds-work-card--author-avatar" src="//a.academia-assets.com/images/s65_no_pic.png" />Michael Flor</a></div><div class="ds-work-card--detail"><p class="ds-work-card--detail ds2-5-body-sm">2021, USPTO</p></div><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">Computer-implemented systems and methods are described herein for automatically generating questions from text. Text including one or more sentences is received. A sentence, comprising a predicate and one or more arguments associated with the predicate, is parsed from the text. Semantic role labels are assigned to the one or more arguments associated with the predicate. One or more questions are automatically generated relating to the predicate based on the assigned semantic role labels. Each answer to the generated questions is one of the one or more arguments associated with the predicate. </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":67636432,"attachmentType":"pdf","workUrl":"https://www.academia.edu/49252725/Systems_and_methods_for_automatic_generation_of_questions_from_text"}">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":67636432,"attachmentType":"pdf","workUrl":"https://www.academia.edu/49252725/Systems_and_methods_for_automatic_generation_of_questions_from_text"}"><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="67636432" data-landing_url="https://www.academia.edu/49252725/Systems_and_methods_for_automatic_generation_of_questions_from_text" 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="82626077" 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/82626077/Automatic_Question_Generation_and_Evaluation">Automatic Question Generation and Evaluation</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="229289071" href="https://independent.academia.edu/ParthPanchal103">Parth Panchal</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="170119066" href="https://independent.academia.edu/ShwetaPatil183">Shweta Patil</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="229299134" href="https://independent.academia.edu/VeerapathiramoorthyPillai">Veerapathiramoorthy Pillai</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="230075507" href="https://usc.academia.edu/JanakThakkar">Janak Thakkar</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2021</p><p class="ds-related-work--abstract ds2-5-body-sm">Generation of questions from an extract is a very tedious task for humans and an even tougher one for machines. In Automatic Question Generation (AQG), it is extremely important to examine the ways in which this can be achieved with sufficient levels of accuracy and efficiency. The ways in which this can be taken ahead is by using the Natural Language Processing (NLP) to process the input and to work with it for AQG. Using NLP with question generation algorithms the system can generate the questions for better understanding of the text document.The input is pre-processed before actually moving in for the question generation process. The questions formed are first checked for proper context satisfaction with the context of the input to avoid invalid or unanswerable question generation. It is then preprocessed using various NLP based mechanisms like tokenization, named entity recognition(NER) tagging, parts of speech(POS) tagging, etc. The question generation system consists of machin...</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 Question Generation and Evaluation","attachmentId":88270947,"attachmentType":"pdf","work_url":"https://www.academia.edu/82626077/Automatic_Question_Generation_and_Evaluation","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/82626077/Automatic_Question_Generation_and_Evaluation"><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="99202054" 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/99202054/Automated_Question_Generator_using_NLP">Automated Question Generator using NLP</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), 2023</p><p class="ds-related-work--abstract ds2-5-body-sm">The purpose of the Automated Paper Generator is to automatize the winning guide machine with the aid of the help of computerized gadgets and full-fledged laptop code, pleasurable their requirements, simply so their precious facts/data can be maintained for an extended quantity with clean gaining access to and manipulation of the desired software program and hardware are honestly available on the market and easy to discern with. automatic query Paper Generator, as represented above, will result in blunders loss, at ease, reliable, and brief control system. it can help the person to not forget their opportunity sports but rather to concentrate on file preserving. So, it's going to assist an organization in the higher utilization of sources. The enterprise will keep computerized records while not redundant entries. which means that one needn't be distracted by info it is now not applicable while having the ability to acquire the statistics. The goal is to automatize its existing guide gadget by way of the assistance of picked equipment and complete-fledged laptop software, pleasurable their requirements, just so their precious facts/statistics can be preserved for an extended quantity with sincere access to and manipulation of the equal. on the whole, the venture describes the manner to manipulate permanently overall performance and better offerings for the customers. Texts with capacity academic well-worth have ended up on the market through the net. however, the victimization of those new texts in lecture rooms introduces several challenges, one in every of which is that they typically lack compliance with physical activities and assessments. right here, we will be inclined to address part of this task by way of automating the creation of a specific form of assessment object and the use of various questions developing with taxonomies. specially, we concentrate on mechanically generating actual WH queries. Our purpose is to make an automatic gadget if you want to take as enter a text and flip out as output questions for assessing a reader's understanding of the records within the text. The questions would possibly then be supplied to a trainer, who would possibly pick and revise people who she or he judges to be beneficial.</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":"Automated Question Generator using NLP","attachmentId":100353111,"attachmentType":"pdf","work_url":"https://www.academia.edu/99202054/Automated_Question_Generator_using_NLP","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/99202054/Automated_Question_Generator_using_NLP"><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="97331994" 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/97331994/Automation_of_Question_Generation_From_Sentences">Automation of Question Generation From Sentences</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="243849282" href="https://independent.academia.edu/HusamAli30">Husam Ali</a></div><p class="ds-related-work--metadata ds2-5-body-xs">… of QG2010: The Third Workshop on …, 2010</p><p class="ds-related-work--abstract ds2-5-body-sm">Abstract. Question Generation (QG) and Question Answering (QA) are key challenges facing systems that interact with natural languages. 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The input text is broken into tokens and questions are generated. This paper states a standard methodology for automated question generation. It focuses on the examination of both semantic and syntactic format of a sentence. Various NLP libraries such as Spacy, NLTK are used for tokenization, stemming, lemmatization, punctuation. Part of Speech tagging is one of the most significant parts of natural language processing which helps us to find the proper tag for given text. Using these NLP libraries the proposed system performs effectively utilizing paragraphs of text as input. The sy...</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":"Automated Question Generator System Using NLP Libraries","attachmentId":79880242,"attachmentType":"pdf","work_url":"https://www.academia.edu/69986724/Automated_Question_Generator_System_Using_NLP_Libraries","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/69986724/Automated_Question_Generator_System_Using_NLP_Libraries"><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="2632003" 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/2632003/QG2010_The_Third_Workshop_on_Question_Generation_QGSTEC_System_Description_JUQGG_A_Rule_based_approach">QG2010: The Third Workshop on Question Generation: QGSTEC System Description -JUQGG : A Rule based approach </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="1793951" href="https://jadavpur.academia.edu/TapabrataMondal">Tapabrata Mondal</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":"QG2010: The Third Workshop on Question Generation: QGSTEC System Description -JUQGG : A Rule based approach ","attachmentId":30634122,"attachmentType":"pdf","work_url":"https://www.academia.edu/2632003/QG2010_The_Third_Workshop_on_Question_Generation_QGSTEC_System_Description_JUQGG_A_Rule_based_approach","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/2632003/QG2010_The_Third_Workshop_on_Question_Generation_QGSTEC_System_Description_JUQGG_A_Rule_based_approach"><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="14070396" 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/14070396/AUTOMATIC_QUESTION_GENERATION_TECHNIQUES_A_COMPARATIVE_STUDY">AUTOMATIC QUESTION GENERATION TECHNIQUES: A COMPARATIVE STUDY</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="21417763" href="https://bilaspuruniversity.academia.edu/RashmiShrivastava">Rashmi Shrivastava</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="33240277" href="https://independent.academia.edu/jeetendraKumar12">jeetendra Kumar</a></div><p class="ds-related-work--abstract ds2-5-body-sm">Automatic question generation is very important part of Natural Language Processing. Recently question generation has got an immense attention from the researchers. Generating questions automatically and reading assessment is a very complex and tedious task. Questions can be of many types like “wh”, descriptive etc. In manual process of generating questions there may be chances of duplicate question generation. Hence there is a need to develop an automatic question generator which automatically generates questions from input text material using Natural Language Processing techniques. The main motivation of this paper is to provide a comparative analysis of various question generators on the basis of types of question generated, accuracy, used tools and nature of over-generation.</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 QUESTION GENERATION TECHNIQUES: A COMPARATIVE STUDY","attachmentId":38194980,"attachmentType":"pdf","work_url":"https://www.academia.edu/14070396/AUTOMATIC_QUESTION_GENERATION_TECHNIQUES_A_COMPARATIVE_STUDY","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/14070396/AUTOMATIC_QUESTION_GENERATION_TECHNIQUES_A_COMPARATIVE_STUDY"><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="19036236" 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/19036236/Generating_Questions_Automatically_from_Informational_Text">Generating Questions Automatically from Informational Text</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="80405" href="https://cmu.academia.edu/JackMostow">Jack Mostow</a></div><p class="ds-related-work--abstract ds2-5-body-sm">Good readers ask themselves questions during reading. 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We describe the modifications required, and evaluate the approach on informational texts from Project LISTEN&#39;s Reading Tutor.</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":"Generating Questions Automatically from Informational Text","attachmentId":40395221,"attachmentType":"pdf","work_url":"https://www.academia.edu/19036236/Generating_Questions_Automatically_from_Informational_Text","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/19036236/Generating_Questions_Automatically_from_Informational_Text"><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="63427009" 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/63427009/IRJET_AUTOMATIC_QUESTION_GENERATION_SYSTEM">IRJET- AUTOMATIC QUESTION GENERATION SYSTEM</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="31493941" href="https://irjet.academia.edu/IRJET">IRJET Journal</a></div><p class="ds-related-work--metadata ds2-5-body-xs">IRJET, 2021</p><p class="ds-related-work--abstract ds2-5-body-sm">This paper focuses on automatic generation of all possible questions from a content of interest. The main thing is to induce fact-grounded questions about a given content from its associated information. Queries are generated by exploiting the named existent data, the keywords and thus the predicate argument structures of the sentences (along with linguistics rules) present within the given body of textbook. The named entities and the semantic tags are used to identify applicable corridor of a judgment in order to form appropriate questions about them. This paper aims to automate the process of question generation grounded on question templates and Bloom's Taxonomy using Natural Language Processing. The end is to produce an interface for the user to generate questions.</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":"IRJET- AUTOMATIC QUESTION GENERATION SYSTEM","attachmentId":75860684,"attachmentType":"pdf","work_url":"https://www.academia.edu/63427009/IRJET_AUTOMATIC_QUESTION_GENERATION_SYSTEM","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/63427009/IRJET_AUTOMATIC_QUESTION_GENERATION_SYSTEM"><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="44951990" 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/44951990/IRJET_Automatic_Question_Generation_from_Text_A_Survey">IRJET- Automatic Question Generation from Text: A Survey</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="31493941" href="https://irjet.academia.edu/IRJET">IRJET Journal</a></div><p class="ds-related-work--metadata ds2-5-body-xs">IRJET, 2021</p><p class="ds-related-work--abstract ds2-5-body-sm">Students ask questions to satisfy their never-ending questions for getting knowledge. To perform competently assessment of students on their major concepts they learned from the study material. Preparing a set of questions for assessment can be time-consuming for teachers while getting questions from external sources like assessment books or question banks might not be relevant to content studied by students. An example, students ask questions to learn more from their teachers, teachers ask questions to help themselves evaluate the performance of the students, and our day-today lives involve asking questions in conversations. To perform competently assessment of students on their major concepts they learned from the study material. Automatic Question Answer Generation (AQAG) is the technique for generating a correct set of questions and answers from a paragraph, which can be text. Automatic question-answer generation (AQAG) is very important for many educational institutes but yet challenging problems in NLP. It is defined as the task of generating syntactically correct sound, semantically perfect and relevant questions and answers from several input formats like text, paragraphs. Question-Answer generation can be useful in many domains such as online assessment, e-tutoring sessions, chatbot systems, search engines and healthcare for analysing mental health. AQAG has got great consideration from researchers in a field of data science engineering.</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":"IRJET- Automatic Question Generation from Text: A Survey","attachmentId":65482450,"attachmentType":"pdf","work_url":"https://www.academia.edu/44951990/IRJET_Automatic_Question_Generation_from_Text_A_Survey","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/44951990/IRJET_Automatic_Question_Generation_from_Text_A_Survey"><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="114755513" 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/114755513/Text_based_Q_and_A_Automated_Question_Generation_and_Answering_for_Enhanced_Data_Processing">Text-based Q&A: Automated Question Generation and Answering for Enhanced Data Processing</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="95329246" href="https://bracu.academia.edu/HumaionKabirMehedi">Md Humaion Kabir Mehedi</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="179024444" href="https://bracu.academia.edu/EhsanurRahmanRhythm">Ehsanur Rahman Rhythm</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="242732804" href="https://independent.academia.edu/ABDULHALIMHOSAIN">ABDUL HALIM HOSAIN</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="303936413" href="https://independent.academia.edu/TonusreeTrina">Tonusree Trina</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2023 Computer Applications & Technological Solutions (CATS), 2024</p><p class="ds-related-work--abstract ds2-5-body-sm">In the age of information overload, where the world is getting increasingly digital, traditional methods of learning are becoming tedious and extensively outdated. Imagine a system with just a few clicks that can quickly generate perplexing questions and enlightening solutions from a given text. Likewise, this paper represents a groundbreaking system that uses stateof-the-art of natural language processing techniques to analyze subject-specific chapters to create questions and corresponding solutions of varying lengths. The system's versatility as an ideal tool for a wide range of users, including students, researchers, and educators, is a result of its capability to handle a wide range of domains. By offering questions of insight along with appropriate answers, this aforementioned structure demonstrated its extraordinary accuracy and competency in our studies on an array of informational datasets. Altering the learning process and promoting knowledge discovery, this program is flexible in delivering brief or comprehensible solutions to inquiries, having the potential to completely change how individuals interact with written material, whether they are reading for short reference or conducting any depth research. Our suggested framework establishes a dynamic platform for immediate information that enables people to learn substantially more and comprehend any topic in depth. With this leading-edge method, bid goodbye to exhausting manual question generation and get ready to embrace a new era of seamless and fruitful learning with this cutting-edge system.</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-based Q\u0026A: Automated Question Generation and Answering for Enhanced Data Processing","attachmentId":111365286,"attachmentType":"pdf","work_url":"https://www.academia.edu/114755513/Text_based_Q_and_A_Automated_Question_Generation_and_Answering_for_Enhanced_Data_Processing","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/114755513/Text_based_Q_and_A_Automated_Question_Generation_and_Answering_for_Enhanced_Data_Processing"><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":67636432,"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":67636432,"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_67636432" 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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