Statistical Malay dependency parser for knowledge acquisition based on word dependency relation
One of the common problems faced when processing information gathered from any natural language is the 'semantic gap' where the 'meaning' of the sentences is not exactly extracted. In Malay Natural Language Processing (NLP), as our knowledge, there is no existing Malay Parser tha...
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my.uniten.dspace-303752023-12-29T15:47:09Z Statistical Malay dependency parser for knowledge acquisition based on word dependency relation Mohamed H. Omar N. Aziz M.J.A. Rahman S.A. 49964168000 23397755200 36089651800 57195320360 Dependency Grammar Dependency Parser Malay corpus Malay Parser Parser Syntactic Relation One of the common problems faced when processing information gathered from any natural language is the 'semantic gap' where the 'meaning' of the sentences is not exactly extracted. In Malay Natural Language Processing (NLP), as our knowledge, there is no existing Malay Parser that can be used to develop a knowledge acquisition feature to extract 'meaning' from Malay articles based-on syntactic relations. This relation is basically the relation between a word and its dependents. This paper will examine the Dependency Grammar (DG) for developing Malay Grammar Parser and discuss the possibilities of developing probabilistic dependency Malay parser using the projected syntactic relation from annotated English corpus. The English side of a parallel corpus, project the analysis to the second language (Malay). Thus, the rules for adaptation from English DG to Malay DG will be defined. The projected tree structure in Malay will be used in training a stochastic analyzer. The training will produce a set of tree lattices which contains chunks of dependency trees for Malay attached with their probability value. A decoder will be developed to test the lattices. A DG for a new Malay sentence is built by combining the pre-determined lattices according to their plausible highest probability of combination. Final 2023-12-29T07:47:09Z 2023-12-29T07:47:09Z 2011 Conference paper 10.1016/j.sbspro.2011.10.597 2-s2.0-83755171540 https://www.scopus.com/inward/record.uri?eid=2-s2.0-83755171540&doi=10.1016%2fj.sbspro.2011.10.597&partnerID=40&md5=c89747a83af914a3394fbea4eee52ec7 https://irepository.uniten.edu.my/handle/123456789/30375 27 188 193 All Open Access; Gold Open Access Scopus |
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Dependency Grammar Dependency Parser Malay corpus Malay Parser Parser Syntactic Relation Mohamed H. Omar N. Aziz M.J.A. Rahman S.A. Statistical Malay dependency parser for knowledge acquisition based on word dependency relation |
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One of the common problems faced when processing information gathered from any natural language is the 'semantic gap' where the 'meaning' of the sentences is not exactly extracted. In Malay Natural Language Processing (NLP), as our knowledge, there is no existing Malay Parser that can be used to develop a knowledge acquisition feature to extract 'meaning' from Malay articles based-on syntactic relations. This relation is basically the relation between a word and its dependents. This paper will examine the Dependency Grammar (DG) for developing Malay Grammar Parser and discuss the possibilities of developing probabilistic dependency Malay parser using the projected syntactic relation from annotated English corpus. The English side of a parallel corpus, project the analysis to the second language (Malay). Thus, the rules for adaptation from English DG to Malay DG will be defined. The projected tree structure in Malay will be used in training a stochastic analyzer. The training will produce a set of tree lattices which contains chunks of dependency trees for Malay attached with their probability value. A decoder will be developed to test the lattices. A DG for a new Malay sentence is built by combining the pre-determined lattices according to their plausible highest probability of combination. |
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49964168000 |
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49964168000 Mohamed H. Omar N. Aziz M.J.A. Rahman S.A. |
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Conference paper |
author |
Mohamed H. Omar N. Aziz M.J.A. Rahman S.A. |
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Mohamed H. |
title |
Statistical Malay dependency parser for knowledge acquisition based on word dependency relation |
title_short |
Statistical Malay dependency parser for knowledge acquisition based on word dependency relation |
title_full |
Statistical Malay dependency parser for knowledge acquisition based on word dependency relation |
title_fullStr |
Statistical Malay dependency parser for knowledge acquisition based on word dependency relation |
title_full_unstemmed |
Statistical Malay dependency parser for knowledge acquisition based on word dependency relation |
title_sort |
statistical malay dependency parser for knowledge acquisition based on word dependency relation |
publishDate |
2023 |
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1806424377102696448 |
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13.222552 |