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Enabling Interactive Answering of Procedural Questions

A mechanism to enable task oriented procedural question answering system for user assistance in English is presented in this paper. The primary aim is to create an answering “corpus” in a tree-form from unstructured document passages. This corpus is used to respond to the queries interactively to as...

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Autores principales: Maitra, Anutosh, Garg, Shivam, Sengupta, Shubhashis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7298181/
http://dx.doi.org/10.1007/978-3-030-51310-8_7
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author Maitra, Anutosh
Garg, Shivam
Sengupta, Shubhashis
author_facet Maitra, Anutosh
Garg, Shivam
Sengupta, Shubhashis
author_sort Maitra, Anutosh
collection PubMed
description A mechanism to enable task oriented procedural question answering system for user assistance in English is presented in this paper. The primary aim is to create an answering “corpus” in a tree-form from unstructured document passages. This corpus is used to respond to the queries interactively to assist in completing a technical task. Reference manuals, documents or webpages are scraped to identify the sections depicting a “procedure” through machine learning techniques and then an integrated task tree with extracted procedural knowledge from text is generated. The automated mechanism breaks the procedural sections into steps, the appropriate “decision points” are identified, the interactive utterances are generated to gain user inputs and the alternative paths are created to complete the tree. Conventional tree traversal mechanism provides step by step guidance to complete a task. Efficacy of the proposed mechanism is tested on documents collected from three different domains and test results are presented.
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spelling pubmed-72981812020-06-17 Enabling Interactive Answering of Procedural Questions Maitra, Anutosh Garg, Shivam Sengupta, Shubhashis Natural Language Processing and Information Systems Article A mechanism to enable task oriented procedural question answering system for user assistance in English is presented in this paper. The primary aim is to create an answering “corpus” in a tree-form from unstructured document passages. This corpus is used to respond to the queries interactively to assist in completing a technical task. Reference manuals, documents or webpages are scraped to identify the sections depicting a “procedure” through machine learning techniques and then an integrated task tree with extracted procedural knowledge from text is generated. The automated mechanism breaks the procedural sections into steps, the appropriate “decision points” are identified, the interactive utterances are generated to gain user inputs and the alternative paths are created to complete the tree. Conventional tree traversal mechanism provides step by step guidance to complete a task. Efficacy of the proposed mechanism is tested on documents collected from three different domains and test results are presented. 2020-05-26 /pmc/articles/PMC7298181/ http://dx.doi.org/10.1007/978-3-030-51310-8_7 Text en © Springer Nature Switzerland AG 2020 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 Article
Maitra, Anutosh
Garg, Shivam
Sengupta, Shubhashis
Enabling Interactive Answering of Procedural Questions
title Enabling Interactive Answering of Procedural Questions
title_full Enabling Interactive Answering of Procedural Questions
title_fullStr Enabling Interactive Answering of Procedural Questions
title_full_unstemmed Enabling Interactive Answering of Procedural Questions
title_short Enabling Interactive Answering of Procedural Questions
title_sort enabling interactive answering of procedural questions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7298181/
http://dx.doi.org/10.1007/978-3-030-51310-8_7
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