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Arabic dialogue processing and act classification using support vector machine.

Text classification is the technique of grouping documents according to their content into classes and groups. As a result of the vast amount of textual material available online, this procedure is becoming increasingly crucial. The primary challenge in text categorization is enhancing classificatio...

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Main Authors:	Alsubayhay, Abraheem Mohammed Sulayman, Salam, Md. Sah, Mohamed, Farhan
Format:	Article
Language:	English
Published:	Science and Information Organization 2023
Subjects:	T Technology (General) TA Engineering (General). Civil engineering (General)
Online Access:	http://eprints.utm.my/105356/1/AbraheemMohammedSulaymanAlsubayhay2023_ArabicDialogueProcessingandActClassification.pdf http://eprints.utm.my/105356/ http://dx.doi.org/10.14569/IJACSA.2023.0140120
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id	my.utm.105356
record_format	eprints
spelling	my.utm.1053562024-04-24T06:35:51Z http://eprints.utm.my/105356/ Arabic dialogue processing and act classification using support vector machine. Alsubayhay, Abraheem Mohammed Sulayman Salam, Md. Sah Mohamed, Farhan T Technology (General) TA Engineering (General). Civil engineering (General) Text classification is the technique of grouping documents according to their content into classes and groups. As a result of the vast amount of textual material available online, this procedure is becoming increasingly crucial. The primary challenge in text categorization is enhancing classification accuracy. This role is receiving more attention due to its importance in the development of these systems and the categorization of Arabic dialogue processing. In the research, attempts were made to define dialogue processing. It concentrates on classifying words that are used in dialogue. There are various types of dialogue processing, including hello, farewell, thank you, confirm, and apologies. The words are used in the study without context. The proposed approach recovers the properties of function words by replacing collocations with standard number tokens and each substantive keyword with a numerical approximation token. With the use of the linear support vector machine (SVM) technique, the classification method for this study was obtained. The act is classified using the linear SVM technique, and the anticipated accuracy is evaluated against that of alternative algorithms. This study encompasses Arabic dialogue acts corpora, annotation schema, and classification problems. It describes the outcomes of contemporary approaches to classifying Arabic dialogue acts. A custom database in the domains of banks, chat, and airline tickets is used in the research to assess the effectiveness of the suggested solutions. The linear SVM approach produced the best results. © 2023,International Journal of Advanced Computer Science and Applications. All Rights Reserved. Science and Information Organization 2023 Article PeerReviewed application/pdf en http://eprints.utm.my/105356/1/AbraheemMohammedSulaymanAlsubayhay2023_ArabicDialogueProcessingandActClassification.pdf Alsubayhay, Abraheem Mohammed Sulayman and Salam, Md. Sah and Mohamed, Farhan (2023) Arabic dialogue processing and act classification using support vector machine. International Journal Of Advanced Computer Science And Applications, 14 (1). pp. 179-190. ISSN 2158-107X http://dx.doi.org/10.14569/IJACSA.2023.0140120 DOI: 10.14569/IJACSA.2023.0140120
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
language	English
topic	T Technology (General) TA Engineering (General). Civil engineering (General)
spellingShingle	T Technology (General) TA Engineering (General). Civil engineering (General) Alsubayhay, Abraheem Mohammed Sulayman Salam, Md. Sah Mohamed, Farhan Arabic dialogue processing and act classification using support vector machine.
description	Text classification is the technique of grouping documents according to their content into classes and groups. As a result of the vast amount of textual material available online, this procedure is becoming increasingly crucial. The primary challenge in text categorization is enhancing classification accuracy. This role is receiving more attention due to its importance in the development of these systems and the categorization of Arabic dialogue processing. In the research, attempts were made to define dialogue processing. It concentrates on classifying words that are used in dialogue. There are various types of dialogue processing, including hello, farewell, thank you, confirm, and apologies. The words are used in the study without context. The proposed approach recovers the properties of function words by replacing collocations with standard number tokens and each substantive keyword with a numerical approximation token. With the use of the linear support vector machine (SVM) technique, the classification method for this study was obtained. The act is classified using the linear SVM technique, and the anticipated accuracy is evaluated against that of alternative algorithms. This study encompasses Arabic dialogue acts corpora, annotation schema, and classification problems. It describes the outcomes of contemporary approaches to classifying Arabic dialogue acts. A custom database in the domains of banks, chat, and airline tickets is used in the research to assess the effectiveness of the suggested solutions. The linear SVM approach produced the best results. © 2023,International Journal of Advanced Computer Science and Applications. All Rights Reserved.
format	Article
author	Alsubayhay, Abraheem Mohammed Sulayman Salam, Md. Sah Mohamed, Farhan
author_facet	Alsubayhay, Abraheem Mohammed Sulayman Salam, Md. Sah Mohamed, Farhan
author_sort	Alsubayhay, Abraheem Mohammed Sulayman
title	Arabic dialogue processing and act classification using support vector machine.
title_short	Arabic dialogue processing and act classification using support vector machine.
title_full	Arabic dialogue processing and act classification using support vector machine.
title_fullStr	Arabic dialogue processing and act classification using support vector machine.
title_full_unstemmed	Arabic dialogue processing and act classification using support vector machine.
title_sort	arabic dialogue processing and act classification using support vector machine.
publisher	Science and Information Organization
publishDate	2023
url	http://eprints.utm.my/105356/1/AbraheemMohammedSulaymanAlsubayhay2023_ArabicDialogueProcessingandActClassification.pdf http://eprints.utm.my/105356/ http://dx.doi.org/10.14569/IJACSA.2023.0140120
_version_	1797906002936332288
score	13.211869

Arabic dialogue processing and act classification using support vector machine.

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