• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1169-1174
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• 2000

Human-compute interface (HCl) should be designed with ease and flexibility for users for providing convenience and friendliness to users. The natural language processing is one of the aspects of HCl. This paper presents the method of design and implementation of SENKOV( Semantic Networks for Korean Verbs) System, which deals with isa hierarchies of Korean verbs for the natural language processing. The system's architecture is based on the differential theory and Levin verb classes. This paper selects about 600 Korean verbs which are commonly used in the daily life, and implements the SENKOV System. The experiments show that SENKOV has 44 top nodes and depth of about 2.35. In addition this paper applied the SENKOV System to co-occurrence constraint relationship among a adverbs and verbs, and proves the validity of the system. This paper is important in that it has made the first trial to classify Korean verb concept for HCl.

• Information Systems Review
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• v.2 no.2
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• pp.245-253
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• 2000

The paper presents methodology and techniques for design and implementation of the SENKOV System based on the validation of set membership and dictionaries. And it performs verb concept classification available for establishing the selectional restriction relationships among adverbs and verbs. The paper is important in that it has made the first attempt at classifying Korean verb concepts for the semantic analysis. We select about 600 Korean verbs which are commonly used in the daily life, and implements the SENKOV System. According to results of the experiments, SENKOV has 44 top nodes and depth of average 2.35, and that it can be utilized to classify Korean verb concept for the selectional restrictions among adverbs and verbs.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.177-179
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• 1998

본 논문은 의미론적 어휘개념에 기반한 한국어 동사 Isa 계층구조 시스템을 이용한 Semantic Network을 구축하며, 이를 활용하여 부사와 동사 간의 공기제약관계 설정에 유효한 개념 분류를 수행한다. 일반적으로 많이 쓰이는 한국어 동사 658개를 대상으로 semantic network을 구축한 결과, SENKOV는 44개의 top node를 가지고 있으며 depth 는 약 2.35이었다. 한국어 동사의 semantic network은 영어에서와 마찬가지로 명사보다 top node의 개수가 많고 depth가 훨씬 더 얕았다. 그리고 성상부사의 selectional restriction에 유효한 개념분류를 하는데 SENKOV를 활용하였다.

• Journal of Information Technology Applications and Management
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• v.9 no.2
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• pp.71-80
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• 2002

Automatic language translation has greatly advanced due to the increased user needs and Information retrieval in WWW. This paper utilizes the integrated knowledge bases of noun and verb networks for automatic translation of ambiguous words in the Korean sentences, through the selectional restriction relation in the sentences. And this paper presents the method to verify validity of Korean noun semantic networks that are used for the construction of the selectional restriction relation by applying the networks to the syntactic and semantic properties Integration of Korean Noun Networks into the SENKOV system will provide the accurate and efficient knowledge bases for the semantic analysis of Korean NLP.