• The Journal of the Korea Contents Association
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• v.12 no.6
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• pp.41-47
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• 2012

Various Korean word sense disambiguation methods have been proposed using small scale of sense-tagged corpra and dictionary definitions to calculate entropy information, conditional probability, mutual information and etc. for each method. This paper proposes a method using Korean Word Space model which builds word vectors from a large scale of sense-tagged corpus and disambiguates word senses with the similarity calculation between the word vectors. Experiment with Sejong morph sense-tagged corpus showed 94% precision for 200 sentences(583 word types), which is much superior to the other known methods.

• Korean Journal of Cognitive Science
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• v.17 no.4
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• pp.255-269
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• 2006

The purpose of this study is to analyze newspaper articles from corpus linguistic point of view. We used a large corpus of newspaper articles built from <21st century Sejong Project> and counted occurrences of certain expressions. A newspaper article is divided into the headline, the lead and the body. We tried to figure out how to measure the characteristics of indication and compression which are typical to headlines. Then, we focused on the differences between the headline and the lead. finally, we analyzed the sentence structure and measured the ratio of the frequency of common nouns in the body. This study verifies the existing stylistic theories of newspapers and shows new aspects of language use in newspaper articles. Texts like newspaper articles are the results of human language processing and they in turn affect the development of cognitive ability of language.