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Automatic question generation: a review of methodologies, datasets, evaluation metrics, and applications
Question generation in natural language has a wide variety of applications. It can be a helpful tool for chatbots for generating interesting questions as also for automating the process of question generation from a piece of text. Most modern-day systems, which are conversational, require question g...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9886210/ http://dx.doi.org/10.1007/s13748-023-00295-9 |
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author | Mulla, Nikahat Gharpure, Prachi |
author_facet | Mulla, Nikahat Gharpure, Prachi |
author_sort | Mulla, Nikahat |
collection | PubMed |
description | Question generation in natural language has a wide variety of applications. It can be a helpful tool for chatbots for generating interesting questions as also for automating the process of question generation from a piece of text. Most modern-day systems, which are conversational, require question generation ability for identifying the user’s needs and serving customers better. Generating questions in natural language is now, a more evolved task, which also includes generating questions for an image or video. In this review, we provide an overview of the research progress in automatic question generation. We also present a comprehensive literature review covering the classification of Question Generation systems by categorizing them into three broad use-cases, namely standalone question generation, visual question generation, and conversational question generation. We next discuss the datasets available for the same for each use-case. We further direct this review towards applications of question generation and discuss the challenges in this field of research. |
format | Online Article Text |
id | pubmed-9886210 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-98862102023-01-31 Automatic question generation: a review of methodologies, datasets, evaluation metrics, and applications Mulla, Nikahat Gharpure, Prachi Prog Artif Intell Review Question generation in natural language has a wide variety of applications. It can be a helpful tool for chatbots for generating interesting questions as also for automating the process of question generation from a piece of text. Most modern-day systems, which are conversational, require question generation ability for identifying the user’s needs and serving customers better. Generating questions in natural language is now, a more evolved task, which also includes generating questions for an image or video. In this review, we provide an overview of the research progress in automatic question generation. We also present a comprehensive literature review covering the classification of Question Generation systems by categorizing them into three broad use-cases, namely standalone question generation, visual question generation, and conversational question generation. We next discuss the datasets available for the same for each use-case. We further direct this review towards applications of question generation and discuss the challenges in this field of research. Springer Berlin Heidelberg 2023-01-30 2023 /pmc/articles/PMC9886210/ http://dx.doi.org/10.1007/s13748-023-00295-9 Text en © Springer-Verlag GmbH Germany, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Review Mulla, Nikahat Gharpure, Prachi Automatic question generation: a review of methodologies, datasets, evaluation metrics, and applications |
title | Automatic question generation: a review of methodologies, datasets, evaluation metrics, and applications |
title_full | Automatic question generation: a review of methodologies, datasets, evaluation metrics, and applications |
title_fullStr | Automatic question generation: a review of methodologies, datasets, evaluation metrics, and applications |
title_full_unstemmed | Automatic question generation: a review of methodologies, datasets, evaluation metrics, and applications |
title_short | Automatic question generation: a review of methodologies, datasets, evaluation metrics, and applications |
title_sort | automatic question generation: a review of methodologies, datasets, evaluation metrics, and applications |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9886210/ http://dx.doi.org/10.1007/s13748-023-00295-9 |
work_keys_str_mv | AT mullanikahat automaticquestiongenerationareviewofmethodologiesdatasetsevaluationmetricsandapplications AT gharpureprachi automaticquestiongenerationareviewofmethodologiesdatasetsevaluationmetricsandapplications |