Legal-Onto: An ontology-based model for representing the knowledge of a legal document
In the legal knowledge domain, legal norm documents are general rules which are mandatory for people in a certain field. Many regulations are affecting to activities in a field. Ontology is an effective approach for representing practical knowledge domains. In this paper, an integration ontology for...
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my.utm.1005202023-04-14T02:45:12Z http://eprints.utm.my/id/eprint/100520/ Legal-Onto: An ontology-based model for representing the knowledge of a legal document Nguyen, Thinh H. Nguyen, Hien D. Pham, Vuong T. Tran, Dung A. Selamat, Ali T Technology (General) In the legal knowledge domain, legal norm documents are general rules which are mandatory for people in a certain field. Many regulations are affecting to activities in a field. Ontology is an effective approach for representing practical knowledge domains. In this paper, an integration ontology for representing the knowledge of a law document is proposed. This model is integrated of ontology about relational knowledge and the graph of keyphrases as a conceptual graph. It can represent semantic of contents in the law document. Based on this integrated model, the improvement method of self-attention network by language-oriented semantic analyzing is studied for intellectual retrieval on the law document. Moreover, the proposed method is applied to construct an intelligent support system for knowledge querying on Vietnam Land Law. It can help users to query some meaning of terminology in land law and some land-related administrative procedures. 2022 Conference or Workshop Item PeerReviewed Nguyen, Thinh H. and Nguyen, Hien D. and Pham, Vuong T. and Tran, Dung A. and Selamat, Ali (2022) Legal-Onto: An ontology-based model for representing the knowledge of a legal document. In: 17th International Conference on Evaluation of Novel Approaches to Software Engineering, ENASE 2022, 25 - 26 April 2022, Virtual, Online. http://dx.doi.org/10.5220/0011066300003176 |
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T Technology (General) Nguyen, Thinh H. Nguyen, Hien D. Pham, Vuong T. Tran, Dung A. Selamat, Ali Legal-Onto: An ontology-based model for representing the knowledge of a legal document |
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In the legal knowledge domain, legal norm documents are general rules which are mandatory for people in a certain field. Many regulations are affecting to activities in a field. Ontology is an effective approach for representing practical knowledge domains. In this paper, an integration ontology for representing the knowledge of a law document is proposed. This model is integrated of ontology about relational knowledge and the graph of keyphrases as a conceptual graph. It can represent semantic of contents in the law document. Based on this integrated model, the improvement method of self-attention network by language-oriented semantic analyzing is studied for intellectual retrieval on the law document. Moreover, the proposed method is applied to construct an intelligent support system for knowledge querying on Vietnam Land Law. It can help users to query some meaning of terminology in land law and some land-related administrative procedures. |
format |
Conference or Workshop Item |
author |
Nguyen, Thinh H. Nguyen, Hien D. Pham, Vuong T. Tran, Dung A. Selamat, Ali |
author_facet |
Nguyen, Thinh H. Nguyen, Hien D. Pham, Vuong T. Tran, Dung A. Selamat, Ali |
author_sort |
Nguyen, Thinh H. |
title |
Legal-Onto: An ontology-based model for representing the knowledge of a legal document |
title_short |
Legal-Onto: An ontology-based model for representing the knowledge of a legal document |
title_full |
Legal-Onto: An ontology-based model for representing the knowledge of a legal document |
title_fullStr |
Legal-Onto: An ontology-based model for representing the knowledge of a legal document |
title_full_unstemmed |
Legal-Onto: An ontology-based model for representing the knowledge of a legal document |
title_sort |
legal-onto: an ontology-based model for representing the knowledge of a legal document |
publishDate |
2022 |
url |
http://eprints.utm.my/id/eprint/100520/ http://dx.doi.org/10.5220/0011066300003176 |
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1764222578616958976 |