• Journal of Digital Convergence
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• v.13 no.5
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• pp.187-194
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• 2015

Various linguistic knowledge resources are required in order that machine can understand diverse variation in natural languages. This paper aims to devise an automatic construction method of linguistic resources by reflecting characteristics of online contents toward continuous expansion. Especially we focused to build NE(Named-Entity) dictionary because the applicability of NEs is very high in linguistic analysis processes. Based on the investigation on Korean Wikipedia, we suggested an efficient construction method of NE dictionary using the syntactic patterns and structural features such as metadatas.

• Language and Information
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• v.6 no.2
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• pp.33-55
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• 2002

This research aims at transforming the definition tort of an English-English-Korean Dictionary (EEKD) which is encoded in EST files for the purpose of publishing into a structured format for Lexical Data Base (LDB). The construction of LDB is very time-consuming and expensive work. In order to save time and efforts in building new lexical information, the present study tries to extract useful linguistic information from an existing printed dictionary. In this paper, the process of extraction and structuring of lexical information from a printed dictionary (EEKD) as a lexical resource is described. The extracted information is represented in XML format, which can be transformed into another representation for different application requirements.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.252-254
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• 2011

본 연구에서는 온라인 사용자 후기글 혹은 상품평관련 사이트에서 나타나는 '질의(Ouery)'가 무엇에 대한 것인지를 분석하고, 그 초점을 제시하는 시스템의 구현을 위하여 요구되는 언어자원을 구축하는 것을 목적으로 한다. 이를 위해 개상의 상태 혹은 성질을 나타내는 의문사 '어떠하' 질의문 유형을 추출하여 여기에서 실현되는 질의초점 명사구에 대한 어휘 사전 및 통사 패턴 LGG문법을 구축하여 질의문의 초점 분석을 위한 체계적인 언어자원 구축의 필요성을 강조하였다. 이와 같이 구축된 LGG문법과 초점어휘 사전의 성능평가를 위해 실험을 수행하였고, 재현률 59%와 정확률 98%의 실험결과를 얻었다.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.93-99
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• 2006

Ontology is an indispensable component in intelligent and semantic processing of knowledge and information, such as in semantic web. Ontology is considered to be constructed generally on the basis of taxonomy of human concepts about the world. However. as human concepts are unstructured and obscure, ontology construction based on the taxonomy of human concepts cannot be realized systematically furthermore automatically. So, we try to do this from the relation among linguistic symbols regarded representing human concepts, in short, words. We show the similarity between taxonomy of human concepts and relation among words. And we propose a methodology to construct and generate automatically ontologies from these relations mon words and a series of algorithm to convert these relations into ontologies. This paper presents the process and concrete application of this methodology.