• Journal of KIISE:Software and Applications
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• v.27 no.7
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• pp.769-783
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• 2000

In this paper, in order to disambiguate Korean noun word sense, we define a local context and explain how to extract it from a raw corpus. Following the intuition that two different nouns are likely to have similar meanings if they occur in the same local context, we use, as a clue, the word that occurs in the same local context where the target noun occurs. This method increases the usability of extracted knowledge and makes it possible to disambiguate the sense of infrequent words. And we can overcome the data sparseness problem by extending the verbs in a local context. The sense of a target noun is decided by the maximum similarity to the clues learned previously. The similarity between two words is computed by their concept distance in the sense hierarchy borrowed from WordNet. By reducing the multiplicity of clues gradually in the process of computing maximum similarity, we can speed up for next time calculation. When a target noun has more than two local contexts, we assign a weight according to the type of each local context to implement the differences according to the strength of semantic restriction of local contexts. As another knowledge source, we get a co-occurrence information from dictionary definitions and example sentences about the target noun. This is used to support local contexts and helps to select the most appropriate sense of the target noun. Through experiments using the proposed method, we discovered that the applicability of local contexts is very high and the co-occurrence information can supplement the local context for the precision. In spite of the high multiplicity of the target nouns used in our experiments, we can achieve higher performance (89.8%) than the supervised methods which use a sense-tagged corpus.

• KIISE Transactions on Computing Practices
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• v.22 no.2
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• pp.107-112
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• 2016

The Sejong Electronic(machine-readable) Dictionary, developed by the 21st century Sejong Plan, contains systematically organized information on Korean words. It helps to solve problems encountered in the electronic formatting of the still-commonly-used hard-copy dictionary. The Sejong Electronic Dictionary, however has a limitation relate to sentence structure and selection-restricted nouns. This paper discuses the limitations of word-sense disambiguation(WSD) that uses subcategorization information suggested by the Sejong Electronic Dictionary and generalized selection-restricted nouns from the Korean Lexico-semantic network. An alternative method that utilized semi-supervised learning, the chi-square test and some other means to make WSD decisions is presented herein.

• Journal of Biomedical Engineering Research
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• v.20 no.6
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• pp.621-627
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• 1999

본 논문은 언어장애인을 위한 통신보조기기의 구현에 관한 연구이다. 통신보조기기에 적용되는 어휘는 사용자의 환경을 고려하여 선택되어야 하며 사용자의 환경에는 연령, 교육정도, 가족관계, 자주 이용하는 장소, 장애의 종류와 정도 등 사용자의 정신적, 육체적 능력을 모두 포함하여야 한다. 본 논문에서는 손의 사용이 가능하고, 어휘와 의미심볼의 관게를 이해할 수 있으면서, 음성표현이 부자유스러운 어린이를 사용자로 한정하였다. 사용자에 의해 발훼된 어휘는 중심어휘와 특정환경을 나타내는 장소 도메인에서의 사용어휘로 나눌 수 있다. 중심어휘는 장소에 구애받지 않고 일상생활에서 널리 쓰이는 어휘를 말하며, 장소 도메인에서의 사용어휘로 나눌 수 있다. 중심어휘는 장소에 구애받지 않고 일상생활에서 널리 쓰이는 어휘를 말하며, 장소 도메인에서의 사용어휘는 특정 장소에서 빈번히 사용하는 어휘를 말한다. 발췌된 어휘는 휴대용 통신보조기기로서의 공간적 제약을 극복하기 위하여 어휘를 명사, 동사, 조사로 나누어 좀더 많은 문장을 만들 수 있도록 하였으며, 동적 시스템과 정적시스템의 장점을 고려하여 장소 도메인 별 어휘로 나누면서 의미함축의 원리를 도입하였다. 또한 어휘의 인식이 쉽도록 의미심볼과 어휘를 대응하여 표현하였고, 시스템의 기능 혹은 어휘분류에 따른 화면의 배경색을 다르게 설정하여 쉽게 사용자가 선택할 수 있도록 하였으며 , 사용자의 선택에 의해 구성된 문장은 화면표시관에 보여진 후 음성으로 표현하였다.

• Phonetics and Speech Sciences
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• v.13 no.2
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• pp.27-35
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• 2021

This study investigated the status of the wh-island constraint in Seoul Korean. The syntactic movement of a wh-phrase out of an embedded sentence so as to have wide scope at LF is known to be invalid as it violates the wh-island constraint, but there have been studies in which such a movement was possible when the sentence is read with a wh-intonation. We conducted perceptual tests in which subjects were asked to select an answer after listening to each of the four types of interrogative sentences. Three of them were with 'Nugu-leul', which is an accusative form of the wh-phrase 'who' as well as an indefinite form. The fourth sentence contained the name of a person. 'Nugu-leul' and the noun were positioned in the same embedded sentence to see whether the subjects accepted a matrix scope interpretation of the wh-phrases. Response time was transformed to normalized log response time and checked to find any differences in the time taken to select the answers depending on different types of interrogative sentences. The results showed the subjects had a definite preference for the matrix scope interpretation for the sentences with a wh-intonation. The response time required to select the matrix scope interpretation was longer than for any other type of interrogative sentence. We concluded that the wh-island constraint in Seoul Korean is weak.

• Annual Conference on Human and Language Technology
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• 2014.10a
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• pp.18-23
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• 2014

한국어 맞춤법 검사기는 전자화된 한국어 텍스트에 나타난 오류어를 검색하여 이를 교정할 대치어를 제시하는 시스템이다. 이때 오류어의 유형은 크게 단순 철자오류와 문맥의존 철자오류로 구분할 수 있다. 이중 문맥의존 철자오류는 어절(word)단위로 봤을 때는 정확하지만, 문맥을 고려하였을 때 오류가 되는 유형으로 교정 난도가 매우 높다. 문맥의존 철자오류의 교정 방법은 크게 규칙을 이용한 방법과 통계 정보에 기반을 둔 방법으로 나뉜다. 이때 규칙을 이용한 방법은 그 특성상 정확도가 매우 높지만, 반대로 재현율이 매우 낮다. 본 논문에서는 본 연구진이 기존에 연구하였던 규칙을 일반화하는 방식에 추가로 조건부 확률을 이용한 통계 방식을 결합하여 정확도를 유지하면서 재현율을 향상시키는 방법을 제안한다.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.3
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• pp.364-372
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• 2000

Subcategorization, defining dependency relation between predicates and their complements, is an important source of knowledge for resolving syntactic and semantic ambiguities arising in analyzing sentences. This paper describes a Korean subcategorization dictionary, particularly annotated with semantic roles of complements coupled with thesaural semantic hierarchy as well as syntactic dependencies. For annotating roles, we defined 25 semantic roles associated with surface case markers that can be used to derive semantic structures directly from syntactic ones. In addition, we used more than 120,000 entries of thesaurus to specify concept markers of noun complements, and also used 47 and 17 predicate patterns for verbs and adjectives, respectively, to express dependency relation between predicates and their complements. Using a full-fledged thesaurus for specifying concept markers makes it possible to build an effective selectional restriction mechanism coupled with the subcategorization dictionary, and using the standard predicate patterns for specifying dependency relations makes it possible to avoid inconsistency in the results and to reduce the costs for constructing the dictionary. On the bases of these, we built a Korean subcategorization dictionary for frequently used 13,000 predicates found in corpora with the aid of a tool specially designed to support this task. An experimental result shows that this dictionary can provide 72.7% of predicates in corpora with appropriate subcategorization information.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.6
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• pp.219-230
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• 2014

An analysis of dependency relation is a job that determines the governor and the dependent between words in sentence. The dependency relation of predicate is established by patterns and selectional restriction of subcategorization of the predicate. This paper proposes a method of analysis of Korean dependency relation using homograph predicate disambiguated in morphology analysis phase. The disambiguated homograph predicates has each different pattern. Especially reusing a stage transition training dictionary used during tagging POS and homograph, we propose a method of fixing the dependency relation of {noun+postposition, predicate}, and we analyze the accuracy and an effect of homograph for analysis of dependency relation. We used the Sejong Phrase Structured Corpus for experiment. We transformed the phrase structured corpus to dependency relation structure and tagged homograph. From the experiment, the accuracy of dependency relation by disambiguating homograph is 80.38%, the accuracy is increased by 0.42% compared with one of undisambiguated homograph. The Z-values in statistical hypothesis testing with significance level 1% is ${\mid}Z{\mid}=4.63{\geq}z_{0.01}=2.33$. So we can conclude that the homograph affects on analysis of dependency relation, and the stage transition training dictionary used in tagging POS and homograph affects 7.14% on the accuracy of dependency relation.