• 음성과학
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• 제8권4호
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• pp.259-273
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• 2001

This study investigates the accentual realization of negation denying the presupposition of a previous utterance compared with that of a general negation. Specifically we study what types and positions of accent are realized in the speech of Korean speakers using English as a second language as well as English native speakers. Gussenhoven (1983) and Bolinger (1985, 1986) suggested that when presupposition of previous utterances is denied through negation, focal accent is assigned to empty (functional) words, rather than negative morphemes. The results of this study, however, show that negation sentences denying presupposition have accents not only on empty (functional) words but also on content words. Almost every English native speaker places an H* accent on the negative morphemes themselves (not, no, nothing, etc.) in general negation, as well as on the other lexical items-verbs and prepositions in our data-in negations denying presuppositions. On the other hand, Korean speakers hardly distinguish between the two kinds of negation sentences, unlike native speakers through accentual differences. Rather, they give accent an every content word, including the negative morphemes in both general negations and negations denying presuppositions. Therefore, the results of this study do not absolutely support the previous studies on the denial of presupposition.

• 한국언어정보학회지:언어와정보
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• 제19권1호
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• pp.37-57
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• 2015

This paper is primarily intended to provide a new insight on which the structural properties of As-Parenthetical constructions shown by Potts (2002) might be regarded as cross-linguistically common one. As a first attempt, it introduces the characteristics of Korean As-Parenthetical by carefully investigating them through the data, focusing on the similarities or differences between two languages with a constructional theoretical perspective. The paper here provides three properties of Korean as-clauses in the morphological and syntactic aspects. First, the morpheme 'as' in English as-clause would be realized as three different morphemes as a bound one. Korean as-clauses can be introduced by three different morphemes, '-tusi, -chelem, -taylo' and unlike that in English as-clauses, they behave as bound morphemes which do not stand alone. Even though they are attached into different morpho-syntactic stems, they do not make any meaning change only under this clause. Secondly, two syntactic types of as-clauses can also be found in Korean, similarly to those of English: CP-As type and Predicate-As type, depending on which types of gap they involve in. English has one more subtype of Predicate-As type (called inverted Predicate-As clause), while Korean does not show this subtype. Thirdly, the various mismatches attributed by the gap and the antecedent come from the constructional restrictions of as-clauses in Korean. In addition, the paper attempts to display various ambiguities from the as-clauses through disjoint references or negative sentences in As-Parenthetical constructions.

• 대한간호학회지
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• 제44권3호
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• pp.328-338
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• 2014

Purpose: This study was done to explore experiences of persons living through the periods of cancer diagnosis, treatment, and self-care. Methods: With permission, texts of 29 cancer survival narratives (8 men and 21 women, winners in contests sponsored by two institutes), were analyzed using Kang's Korean-Computerized-Text-Analysis-Program where the commonly used Korean-Morphological-Analyzer and the 21st-century-Sejong-Modern-Korean-Corpora representing laymen's Korean-language-use are connected. Experiences were explored based on words included in 100 highly-used-morphemes. For interpretation, we used 'categorizing words by meaning', 'comparing use-rate by periods and to the 21st-century-Sejong-Modern-Korean-Corpora', and highly-used-morphemes that appeared only in a specific period. Results: The most highly-used-word-morpheme was first-person-pronouns followed by, diagnosis treatment-related- words, mind-expression-words, cancer, persons-in-meaningful-interaction, living and eating, information-related-verbs, emotion-expression- words, with 240 to 0.8 times for layman use-rate. 'Diagnosis-process', 'cancer-thought', 'things-to-come-after-diagnosis', 'physician husband', 'result-related-information', 'meaningful-things before diagnosis-period', and 'locus-of-cause' dominated the life of the diagnosis-period. 'Treatment', 'unreliable-body', 'husband people mother physician', 'treatment-related-uncertainty', 'hard-time', and 'waiting-time represented experiences in the treatment-period. Themes of living in the self-care-period were complex and included 'living-as-a-human', 'self-managing-of-diseased-body', 'positive-emotion', and 'connecting past present future'. Conclusion: The results show that the experience of living for persons with cancer is influenced by each period's own situational-characteristics. Experiences of the diagnosis and treatment-period are negative disease-oriented while that of the self-care period is positive present-oriented.

• 한국IT서비스학회지
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• 제17권1호
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• pp.79-89
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• 2018

Sentiment analysis is a technique of text mining that extracts feelings of the person who wrote the sentence like movie review. The preliminary researches of sentiment analysis identify sentiments by using the dictionary which contains negative and positive words collected in advance. As researches on deep learning are actively carried out, sentiment analysis using deep learning model with morpheme or word unit has been done. However, this model has disadvantages in that the word dictionary varies according to the domain and the number of morphemes or words gets relatively larger than that of phonemes. Therefore, the size of the dictionary becomes large and the complexity of the model increases accordingly. We construct a sentiment analysis model using recurrent neural network by dividing input data into phoneme-level which is smaller than morpheme-level. To verify the performance, we use 30,000 movie reviews from the Korean biggest portal, Naver. Morpheme-level sentiment analysis model is also implemented and compared. As a result, the phoneme-level sentiment analysis model is superior to that of the morpheme-level, and in particular, the phoneme-level model using LSTM performs better than that of using GRU model. It is expected that Korean text processing based on a phoneme-level model can be applied to various text mining and language models.

• 한국콘텐츠학회논문지
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• 제16권10호
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• pp.393-402
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• 2016

기상청에서 현재 시행되고 있는 만족도 설문조사의 한계를 보완하기 위해 SNS를 통한 감성분석이 활용될 수 있다. 감성분석은 2011~2014년 동안 '기상청'을 언급한 트위터를 수집하여 나이브 베이즈 방법으로 긍정, 부정, 중립 감성을 분류하였다. 기본적인 나이브 베이즈 방법에 긍정, 부정, 중립의 각 감성에서만 출현한 형태소들로 추가사전을 만들어 감성분석의 정확도를 향상시키는 방법을 제안하였다. 분석결과 기본적인 나이브 베이즈 방법으로 감성을 분류할 경우 약 75%의 정확도로 학습데이터를 재현한데 반해 추가 사전을 적용할 경우 약 97%의 정확성을 보였다. 추가사전을 활용하여 검증자료의 감성을 분류한 결과 약 75%의 분류 정확도를 보였다. 낮은 분류 정확도는 향후 기상 관련의 다양한 키워드를 포함시켜 학습데이터 양을 늘려 감성사전의 질을 높임과 동시에 상시적인 사전의 업데이트를 통해 개선될 수 있을 것이다. 한편, 개별 어휘의 사전적 의미에 기반한 감성분석과 달리 문장의 의미에 기반하여 감성을 분류할 경우 부정적 감성 비율의 증가와 만족도 변화 추이를 설명할 수 있을 것으로 보여 향후 설문조사를 보완할 수 있는 좋은 수단으로 SNS를 통한 감성분석이 활용될 수 있을 것으로 사료된다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제30권1_2호
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• pp.173-183
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• 2003

형태소 분석을 한 후 명사를 추출하는 방법은 모든 어절에 대해 빈번한 사전 참조와 음운 복원을 위한 규칙 적용을 수행하므로 많은 연산을 필요로 하고, 중의성이 있는 어절에 대해 모든 가능한 분석결과를 생성하므로 명사 추출의 관점에서는 비효율적이다. 본 논문에서는 명사 추출의 관점에서 형태소 분석시 불필요한 연산을 줄이기 위해 명사 출현 특성을 고려하는 명사 추출 방법을 제안한다. 명사 출현 특성은 명사의 존재에 대한 긍정적 또는 부정적인 단서를 표현하는 한국어의 특성으로서, 배제 정보와 명사 접미 음절열이 있다. 배제 정보는 명사가 잃는 어절을 미리 배제하여 형태소 분석에 요구되는 탐색 공간을 줄이고. 명사 접미 음절열은 바로 알에 있는 병사를 검사함으로써 단순한 방법으로 명사를 추출하거나 미등록어를 인식하는 데에 사용한다. 또한 본 논문에서는 형태소 분석시 복잡한 음운 현상을 처리하기 위해 많은 음운 규칙을 적용하는 대신 음운 복인 정보를 사용하여 음운 현상을 처리한다. 실험 결과에 의하면 덕 방법은 기존의 형태소 분석 방법에 의한 명사 추출에 비해 정확도는 떨어지지 않으면서 수행 속도 면에서 매우 효율적임을 알 수 있다.