• 한국전자통신학회논문지
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• 제7권4호
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• pp.783-787
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• 2012

한 어절을 중심으로 검사가 이루어지는 맞춤법 검사는 문맥상 어울리지 않는 단어로 인하여 생기는 오류는 찾기 어렵다. 맞춤법 검사기는 현재 어절 단위로 오류 여부를 판단하는 것이기 때문에 어휘적 중의성을 고려하지 않아도 된다. 그러나 문법 검사기는 문장 분석을 해야 하므로 어휘적 중의성을 제거하지 않고는 정확한 검사가 어렵다. 본 논문에서는 어휘적 중의성을 해결하기 위하여 몇 가지 규칙을 만들고 이를 활용하여 문장에 존재하는 어휘적 중의성을 해결할 수 있는 방법을 보인다. 또한 실험을 통하여 그 결과를 분석하였다.

• 한국멀티미디어학회논문지
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• 제20권3호
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• pp.533-542
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• 2017

Novels include various character names, depending on the genre and the spatio-temporal background of the novels and the nationality of characters. Besides, characters and their names in a novel are created by the author's pen and imagination. As a result, any proper noun dictionary cannot include all kinds of character names. In addition, the novels translated into Korean have character names consisting of two or more nouns (such as "Harry Potter"). In this paper, we propose a method to extract noun phrases for character names and to cluster the noun phrases into coreferents for the same character name. In the extraction of noun phrases, we utilize KKMA morpheme analyzer and CPFoAN character identification tool. In clustering the noun phrases into coreferents, we construct a directed graph with the character names extracted by CPFoAN and the extracted noun phrases, and then we create name sets for characters by traversing connected subgraphs in the directed graph. With four novels translated into Korean, we conduct a survey to evaluate the proposed method. The results show that the proposed method will be useful for speaker identification as well as for constructing the social network of characters.