Proceedings of the Workshop on Human Language Technology and Knowledge Management - 2001
DOI: 10.3115/1118220.1118226
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Semi-automatic practical ontology construction by using a thesaurus, computational dictionaries, and large corpora

Abstract: This paper presents the semi-automatic construction method of a practical ontology by using various resources. In order to acquire a reasonably practical ontology in a limited time and with less manpower, we extend the Kadokawa thesaurus by inserting additional semantic relations into its hierarchy, which are classified as case relations and other semantic relations. The former can be obtained by converting valency information and case frames from previously-built computational dictionaries used in machine tra… Show more

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Cited by 14 publications
(3 citation statements)
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“…However, A did not possess the Fig. 2 Kadokawa Thesaurus Hierarchy [39] authority(code:449) to conclude the contract(code:448). If B ratifies(code:444) the contract(code:448) of sales, A is not liable(code:449) to C as an unauthorized agency(code:552).…”
Section: Approachmentioning
confidence: 99%
“…However, A did not possess the Fig. 2 Kadokawa Thesaurus Hierarchy [39] authority(code:449) to conclude the contract(code:448). If B ratifies(code:444) the contract(code:448) of sales, A is not liable(code:449) to C as an unauthorized agency(code:552).…”
Section: Approachmentioning
confidence: 99%
“…The author [12] presents an approach based on deep convolutional neural networks for the Alzheimer's disease diagnosis procedure to detect the early stage of the disease (AD). In the biomedical context, little research has been done on aspects related to knowledge related to ontology, they are complex processes that take a lot of time, the research applies approaches based on machine learning with an accuracy of 92.12% and those based on deep learning of convolutional neural networks.…”
Section: Introductionmentioning
confidence: 99%
“…In recent researches, there have been many attempts to construct an ontology automatically or semiautomatically [2,3]. Most of these researches tend to construct an ontology for a general domain.…”
Section: Introductionmentioning
confidence: 99%