A review on learning taxonomies from Malay text corpora
Taxonomy is a science of classifying living things. In the 21st century, taxonomy is also known as a form of business intelligence, used to integrate information, reduce semantic heterogeneity, describe emergent communities and interest groups, facilitate the communication between information system...
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| Format: | Article |
| Language: | en |
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Penerbit UTM Press
2007
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| Online Access: | http://eprints.utm.my/8173/1/SitiMariyamShamsudin2007_AReviewonLearningTaxonomiesfromMalay.pdf http://eprints.utm.my/8173/ |
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| author | Ahmad Nazri, Mohd. Zakree Shamsuddin, Siti Mariyam Abu Bakar, Azuraliza |
| author_facet | Ahmad Nazri, Mohd. Zakree Shamsuddin, Siti Mariyam Abu Bakar, Azuraliza |
| author_sort | Ahmad Nazri, Mohd. Zakree |
| building | UTM Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Malaysia |
| content_source | UTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Taxonomy is a science of classifying living things. In the 21st century, taxonomy is also known as a form of business intelligence, used to integrate information, reduce semantic heterogeneity, describe emergent communities and interest groups, facilitate the communication between information systems. However, in building a taxonomy, knowledge acquisition is the bottleneck that . Ontology engineers also need guidelines about the effectiveness, efficiency and trade-offs of different methods in order to decide which techniques to apply in which settings. But there are no comparative work systematically analyzing different techniques and algorithms on learning concept hierarchies from a Malay text. In this paper we review the state of the arts in taxonomy learning and address the lack of work in the field of concept hierarchy induction from Malay text. We also defme an evaluation methodology to systematically comparing different approaches. In our further works section, we proposed an experimental approach to study various approaches and methods to automatically acquire concept hierarchies from Malay texts. |
| format | Article |
| id | my.utm.eprints-8173 |
| institution | Universiti Teknologi Malaysia |
| language | en |
| publishDate | 2007 |
| publisher | Penerbit UTM Press |
| record_format | eprints |
| spelling | my.utm.eprints-81732017-11-01T04:17:24Z http://eprints.utm.my/8173/ A review on learning taxonomies from Malay text corpora Ahmad Nazri, Mohd. Zakree Shamsuddin, Siti Mariyam Abu Bakar, Azuraliza QM Human anatomy Taxonomy is a science of classifying living things. In the 21st century, taxonomy is also known as a form of business intelligence, used to integrate information, reduce semantic heterogeneity, describe emergent communities and interest groups, facilitate the communication between information systems. However, in building a taxonomy, knowledge acquisition is the bottleneck that . Ontology engineers also need guidelines about the effectiveness, efficiency and trade-offs of different methods in order to decide which techniques to apply in which settings. But there are no comparative work systematically analyzing different techniques and algorithms on learning concept hierarchies from a Malay text. In this paper we review the state of the arts in taxonomy learning and address the lack of work in the field of concept hierarchy induction from Malay text. We also defme an evaluation methodology to systematically comparing different approaches. In our further works section, we proposed an experimental approach to study various approaches and methods to automatically acquire concept hierarchies from Malay texts. Penerbit UTM Press 2007-12 Article PeerReviewed application/pdf en http://eprints.utm.my/8173/1/SitiMariyamShamsudin2007_AReviewonLearningTaxonomiesfromMalay.pdf Ahmad Nazri, Mohd. Zakree and Shamsuddin, Siti Mariyam and Abu Bakar, Azuraliza (2007) A review on learning taxonomies from Malay text corpora. Jurnal Teknologi Maklumat, 19 (2). pp. 85-99. ISSN 0128-3790 |
| spellingShingle | QM Human anatomy Ahmad Nazri, Mohd. Zakree Shamsuddin, Siti Mariyam Abu Bakar, Azuraliza A review on learning taxonomies from Malay text corpora |
| title | A review on learning taxonomies from Malay text corpora
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| title_full | A review on learning taxonomies from Malay text corpora
|
| title_fullStr | A review on learning taxonomies from Malay text corpora
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| title_full_unstemmed | A review on learning taxonomies from Malay text corpora
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| title_short | A review on learning taxonomies from Malay text corpora
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| title_sort | review on learning taxonomies from malay text corpora |
| topic | QM Human anatomy |
| url | http://eprints.utm.my/8173/1/SitiMariyamShamsudin2007_AReviewonLearningTaxonomiesfromMalay.pdf http://eprints.utm.my/8173/ |
| url_provider | http://eprints.utm.my/ |