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Adaptive learning for lemmatization in morphology analysis

Morphological analysis is used to study the internal structure words by reducing the number of vocabularies used while retaining the semantic meaning of the knowledge in NLP system. Most of the existing algorithms are focusing on stemmatization instead of lemmatization process. Even with technology...

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Main Authors: Ting, Mary, Abdul Kadir, Rabiah, Tengku Sembok, Tengku Mohd, Ahmad, Fatimah, Azman, Azreen
Format: Conference or Workshop Item
Published: Springer International Publishing 2014
Online Access:http://psasir.upm.edu.my/id/eprint/40308/
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spelling my.upm.eprints.403082015-09-03T03:27:01Z http://psasir.upm.edu.my/id/eprint/40308/ Adaptive learning for lemmatization in morphology analysis Ting, Mary Abdul Kadir, Rabiah Tengku Sembok, Tengku Mohd Ahmad, Fatimah Azman, Azreen Morphological analysis is used to study the internal structure words by reducing the number of vocabularies used while retaining the semantic meaning of the knowledge in NLP system. Most of the existing algorithms are focusing on stemmatization instead of lemmatization process. Even with technology advancement, yet none of the available lemmatization algorithms able to produce 100 % accurate result. The base words produced by the current algorithm might be unusable as it alters the overall meaning it tried to represent, which will directly affect the outcome of NLP systems. This paper proposed a new method to handle lemmatization process during the morphological analysis. The method consists three layers of lemmatization process, which incorporate the used of Stanford parser API, WordNet database and adaptive learning technique. The lemmatized words yields from the proposed method are more accurate, thus it will improve the semantic knowledge represented and stored in the knowledge base. Springer International Publishing 2014 Conference or Workshop Item NonPeerReviewed Ting, Mary and Abdul Kadir, Rabiah and Tengku Sembok, Tengku Mohd and Ahmad, Fatimah and Azman, Azreen (2014) Adaptive learning for lemmatization in morphology analysis. In: 13th International Conference on Intelligent Software Methodologies, Tools, and Techniques (SOMET 2014), 22-24 Sep. 2014, Langkawi, Malaysia. (pp. 343-357). 10.1007/978-3-319-17530-0_24
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description Morphological analysis is used to study the internal structure words by reducing the number of vocabularies used while retaining the semantic meaning of the knowledge in NLP system. Most of the existing algorithms are focusing on stemmatization instead of lemmatization process. Even with technology advancement, yet none of the available lemmatization algorithms able to produce 100 % accurate result. The base words produced by the current algorithm might be unusable as it alters the overall meaning it tried to represent, which will directly affect the outcome of NLP systems. This paper proposed a new method to handle lemmatization process during the morphological analysis. The method consists three layers of lemmatization process, which incorporate the used of Stanford parser API, WordNet database and adaptive learning technique. The lemmatized words yields from the proposed method are more accurate, thus it will improve the semantic knowledge represented and stored in the knowledge base.
format Conference or Workshop Item
author Ting, Mary
Abdul Kadir, Rabiah
Tengku Sembok, Tengku Mohd
Ahmad, Fatimah
Azman, Azreen
spellingShingle Ting, Mary
Abdul Kadir, Rabiah
Tengku Sembok, Tengku Mohd
Ahmad, Fatimah
Azman, Azreen
Adaptive learning for lemmatization in morphology analysis
author_facet Ting, Mary
Abdul Kadir, Rabiah
Tengku Sembok, Tengku Mohd
Ahmad, Fatimah
Azman, Azreen
author_sort Ting, Mary
title Adaptive learning for lemmatization in morphology analysis
title_short Adaptive learning for lemmatization in morphology analysis
title_full Adaptive learning for lemmatization in morphology analysis
title_fullStr Adaptive learning for lemmatization in morphology analysis
title_full_unstemmed Adaptive learning for lemmatization in morphology analysis
title_sort adaptive learning for lemmatization in morphology analysis
publisher Springer International Publishing
publishDate 2014
url http://psasir.upm.edu.my/id/eprint/40308/
_version_ 1643832678430015488
score 13.211869

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