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...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Published: |
Springer International Publishing
2014
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| Online Access: | http://psasir.upm.edu.my/id/eprint/40308/ |
| _version_ | 1848849389068484608 |
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| author | Ting, Mary Abdul Kadir, Rabiah Tengku Sembok, Tengku Mohd Ahmad, Fatimah Azman, Azreen |
| author_facet | Ting, Mary Abdul Kadir, Rabiah Tengku Sembok, Tengku Mohd Ahmad, Fatimah Azman, Azreen |
| author_sort | Ting, Mary |
| building | UPM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T09:49:37Z |
| format | Conference or Workshop Item |
| id | upm-40308 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T09:49:37Z |
| publishDate | 2014 |
| publisher | Springer International Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-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 |
| spellingShingle | Ting, Mary Abdul Kadir, Rabiah Tengku Sembok, Tengku Mohd Ahmad, Fatimah Azman, Azreen Adaptive learning for lemmatization in morphology analysis |
| title | 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_short | Adaptive learning for lemmatization in morphology analysis |
| title_sort | adaptive learning for lemmatization in morphology analysis |
| url | http://psasir.upm.edu.my/id/eprint/40308/ http://psasir.upm.edu.my/id/eprint/40308/ |