Transferring Informal Text in Arabic as Low Resource Languages: State-of-the-Art and Future Research Directions

Almansor, EH; Al-Ani, A; Hussain, FK

Transferring Informal Text in Arabic as Low Resource Languages: State-of-the-Art and Future Research Directions

Almansor, EH Al-Ani, A

Hussain, FK

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Publisher:: Springer
Publication Type:: Conference Proceeding
Citation:: Complex, Intelligent, and Software Intensive Systems, 2020, 993, pp. 176-187
Issue Date:: 2020-01-01

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Field	Value	Language
dc.contributor.author	Almansor, EH
dc.contributor.author	Al-Ani, A https://orcid.org/0000-0002-8092-8954
dc.contributor.author	Hussain, FK
dc.date	2019-07-03
dc.date.accessioned	2021-05-07T02:15:09Z
dc.date.available	2021-05-07T02:15:09Z
dc.date.issued	2020-01-01
dc.identifier.citation	Complex, Intelligent, and Software Intensive Systems, 2020, 993, pp. 176-187
dc.identifier.isbn	9783030223533
dc.identifier.issn	2194-5357
dc.identifier.issn	2194-5365
dc.identifier.uri	http://hdl.handle.net/10453/148766
dc.description.abstract	Rapid growth in internet technology lead to increase the usage of social media platforms which make communication between users easier. Through the communication users used their daily languages which considered as non-standard language. The non-slandered text contains lots of noise, such as abbreviations, slang which used more in English languages and dialect words which are widely used in Arabic language. These texts face challenging using any natural language processing tools. Therefore, these texts need to be treated and transferred to be similar to their standard form. According to that the normalization and translation approach have been used to transfer the informal text. However, using these approach need large label or parallel datasets. While high resource languages such as English have enough parallel datasets, low resource languages such as Arabic is lack of enough parallel dataset. Therefore, in this paper we focus on the Arabic and Arabic dialects as a low resource language in the era of transferring non-stander text using normalization and translation approach.
dc.language	en
dc.publisher	Springer
dc.relation.ispartof	Complex, Intelligent, and Software Intensive Systems
dc.relation.ispartof	International Conference on Complex, Intelligent, and Software Intensive Systems
dc.relation.ispartofseries	Advances in Intelligent Systems and Computing
dc.relation.isbasedon	10.1007/978-3-030-22354-0_17
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Transferring Informal Text in Arabic as Low Resource Languages: State-of-the-Art and Future Research Directions
dc.type	Conference Proceeding
utslib.citation.volume	993
utslib.location.activity	Australia
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2021-05-07T02:15:08Z
pubs.finish-date	2019-07-05
pubs.place-of-publication	Switzerland
pubs.publication-status	Published
pubs.start-date	2019-07-03
pubs.volume	993
dc.location	Switzerland

Abstract:

Rapid growth in internet technology lead to increase the usage of social media platforms which make communication between users easier. Through the communication users used their daily languages which considered as non-standard language. The non-slandered text contains lots of noise, such as abbreviations, slang which used more in English languages and dialect words which are widely used in Arabic language. These texts face challenging using any natural language processing tools. Therefore, these texts need to be treated and transferred to be similar to their standard form. According to that the normalization and translation approach have been used to transfer the informal text. However, using these approach need large label or parallel datasets. While high resource languages such as English have enough parallel datasets, low resource languages such as Arabic is lack of enough parallel dataset. Therefore, in this paper we focus on the Arabic and Arabic dialects as a low resource language in the era of transferring non-stander text using normalization and translation approach.

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http://hdl.handle.net/10453/148766