Proper noun detection using regex algorithm and rules for malay named entity recognition

Proper noun detection using regex algorithm and rules for malay named entity recognition

This study was aimed to develop a Malay proper noun detection method to cluster andclassify named entity categories, particularly for major important classes such asperson, location, organization, and miscellaneous for Malay newspaper corpus. RegularExpression pattern identification (regex) algorith...

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Main Author: Farid Morsidi
Format: thesis
Language:eng
Published: 2018
Subjects:
QA Mathematics
Online Access:https://ir.upsi.edu.my/detailsg.php?det=5380
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institution Universiti Pendidikan Sultan Idris
collection UPSI Digital Repository
language eng
topic QA Mathematics
spellingShingle QA Mathematics
Farid Morsidi
Proper noun detection using regex algorithm and rules for malay named entity recognition
description This study was aimed to develop a Malay proper noun detection method to cluster andclassify named entity categories, particularly for major important classes such asperson, location, organization, and miscellaneous for Malay newspaper corpus. RegularExpression pattern identification (regex) algorithm and rule were introduced in this study toovercome the limitation of dictionary and gazetteer. Two visualization techniques namely asDecision Tree and Term Document Matrix had been used to evaluate the efficiency of themethod. The result obtained 74% of accuracy during the generation of decision tree. Visualization for term document matrix achieves a maximized value of 9.8007403, 9.8718517, and9.9890683 for Astro Awani, Berita Harian, and Bernama dataset respectively. As a conclusion, theregex algorithm could indicate the presence of Malay proper noun, thus making it an appropriatemethod for extraction tool to cluster and classify Malay proper noun. The study implicates thatthe use of Malay proper noun detection method can increase the effectiveness in namedentity recognition and beneficial to improve document retrieval for Malaylanguage.
format thesis
qualification_name
qualification_level Master's degree
author Farid Morsidi
author_facet Farid Morsidi
author_sort Farid Morsidi
title Proper noun detection using regex algorithm and rules for malay named entity recognition
title_short Proper noun detection using regex algorithm and rules for malay named entity recognition
title_full Proper noun detection using regex algorithm and rules for malay named entity recognition
title_fullStr Proper noun detection using regex algorithm and rules for malay named entity recognition
title_full_unstemmed Proper noun detection using regex algorithm and rules for malay named entity recognition
title_sort proper noun detection using regex algorithm and rules for malay named entity recognition
granting_institution Universiti Pendidikan Sultan Idris
granting_department Fakulti Seni, Komputeran dan Industri Kreatif
publishDate 2018
url https://ir.upsi.edu.my/detailsg.php?det=5380
_version_ 1747833187559538688
spelling oai:ir.upsi.edu.my:53802020-11-19 Proper noun detection using regex algorithm and rules for malay named entity recognition 2018 Farid Morsidi QA Mathematics This study was aimed to develop a Malay proper noun detection method to cluster andclassify named entity categories, particularly for major important classes such asperson, location, organization, and miscellaneous for Malay newspaper corpus. RegularExpression pattern identification (regex) algorithm and rule were introduced in this study toovercome the limitation of dictionary and gazetteer. Two visualization techniques namely asDecision Tree and Term Document Matrix had been used to evaluate the efficiency of themethod. The result obtained 74% of accuracy during the generation of decision tree. Visualization for term document matrix achieves a maximized value of 9.8007403, 9.8718517, and9.9890683 for Astro Awani, Berita Harian, and Bernama dataset respectively. As a conclusion, theregex algorithm could indicate the presence of Malay proper noun, thus making it an appropriatemethod for extraction tool to cluster and classify Malay proper noun. The study implicates thatthe use of Malay proper noun detection method can increase the effectiveness in namedentity recognition and beneficial to improve document retrieval for Malaylanguage. 2018 thesis https://ir.upsi.edu.my/detailsg.php?det=5380 https://ir.upsi.edu.my/detailsg.php?det=5380 text eng closedAccess Masters Universiti Pendidikan Sultan Idris Fakulti Seni, Komputeran dan Industri Kreatif Abdallah, S., Shaalan, K., & Shoaib, M. (2012). Integrating rule-based system with classification for arabic named entity recognition. In Lecture Notes in ComputerScience (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7181 LNCS, pp. 311322).http://doi.org/10.1007/978-3-642-28604- 9_26AbdelRahman, S., Elarnaoty, M., & Magdy, M. (2010). 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