• 영어어문교육
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• 제9권1호
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• pp.131-152
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• 2003

The purpose of this study is to investigate the correlation between the introduction order of 9 English morphemes in the English textbook used in the middle school and the learning order of the morphemes by the 7th graders learning English as a foreign language. The subjects are 139 students in two middle schools, who learn English with different textbooks. The introduction order of each morpheme in two textbooks was examined according to its quantity and frequency. Data on the real learning order were collected through the written SLOPE test, and each morpheme was ranked by its group score. The introduction order of each morpheme in the textbook and the real learning order were analyzed by Spearman rank order correlation. It was shown that the correlation between the two was very low. This means that those textbooks do not take the learning order of English morphemes into account. Also it was shown that in the earlier stage of learning English the introduction order of each morpheme in the textbook had much influence on its learning order, but in the later stage such influence reduced gradually. This means that the learning order of English morphemes approaches the natural order as time passes by.

• 한국언어정보학회지:언어와정보
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• 제18권1호
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• pp.1-32
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• 2014

This paper provides a corpus study on subjunctives in Korean in a way of comparative semantics. The whole arguments of this paper are bolstered by distributional evidence taken from naturally occurring bitexts (i.e. a bilingual corpus), in which one sentence in a language is aligned with one translation in the other language. Since previous studies regard past tense morphology as the main component to express irrealis and uncertainty, this paper accordingly checks out whether the past tense morpheme (e/a)ss in Korean is also responsible for conveying the meaning of subjunctives. My finding is that the past tense morpheme (e/a)ss is a sufficient condition for forming subjunctives in Korean. The current corpus study verifies that the past tense morpheme is not obligatorily used in present conditional counterfactuals in Korean, unlike English. Yet, if (e/a)ss is used and the antecedent denotes a present situation, the conditional sentence can only be interpreted as conveying counterfactuality. On the other hand, wish constructions in Korean, irrespective of the semantic tense, often contain the past tense morpheme. Hence, this work substantiates Iatridou (2000)'s theory of 'fake past tense' is applicable to Korean subjunctives. The present corpus study, additionally, reveals that a conditional marker telamyen is a component of expressing past counterfactuals in Korean.

• 지능정보연구
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• 제24권2호
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• pp.59-83
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• 2018

고객과 대중의 니즈를 파악하기 위한 감성분석의 중요성이 커지면서 최근 영어 텍스트를 대상으로 다양한 딥러닝 모델들이 소개되고 있다. 본 연구는 영어와 한국어의 언어적인 차이에 주목하여 딥러닝 모델을 한국어 상품평 텍스트의 감성분석에 적용할 때 부딪히게 되는 기본적인 이슈들에 대하여 실증적으로 살펴본다. 즉, 딥러닝 모델의 입력으로 사용되는 단어 벡터(word vector)를 형태소 수준에서 도출하고, 여러 형태소 벡터(morpheme vector) 도출 대안에 따라 감성분석의 정확도가 어떻게 달라지는지를 비정태적(non-static) CNN(Convolutional Neural Network) 모델을 사용하여 검증한다. 형태소 벡터 도출 대안은 CBOW(Continuous Bag-Of-Words)를 기본적으로 적용하고, 입력 데이터의 종류, 문장 분리와 맞춤법 및 띄어쓰기 교정, 품사 선택, 품사 태그 부착, 고려 형태소의 최소 빈도수 등과 같은 기준에 따라 달라진다. 형태소 벡터 도출 시, 문법 준수도가 낮더라도 감성분석 대상과 같은 도메인의 텍스트를 사용하고, 문장 분리 외에 맞춤법 및 띄어쓰기 전처리를 하며, 분석불능 범주를 포함한 모든 품사를 고려할 때 감성분석의 분류 정확도가 향상되는 결과를 얻었다. 동음이의어 비율이 높은 한국어 특성 때문에 고려한 품사 태그 부착 방안과 포함할 형태소에 대한 최소 빈도수 기준은 뚜렷한 영향이 없는 것으로 나타났다.

• 한국언어정보학회지:언어와정보
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• 제3권1호
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• pp.1-20
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• 1999

The purpose of this paper is to expand Stowell (1993), Stowell (1995), Stowell (1996)'s syntactic analysis of tense in English. Stowell treats Tense as a dyadic predicate of temporal ordering which takes those two time-denoting phrases as its arguments. He further argues that those two morphemes 'resent' and 'past' are polarity-sensitive elements encoding an LF-scope relation with respect to true PAST tense. This paper proposes that English future 'will' should be treated as a true tense and that its future morpheme is an anti-PAST polarity item. It also provides a syntactic interpretation of a peculiar morphological aspect of English that it has no future form of the verb. To this end, Stowell's analysis is incorporated into the Minimalist program of Chomsky(1995). It is proposed that, unlike in other languages like French and Spanish, FUTURE in English is of an affix. This provides an intuitively correct description of why English verbs do not have a future form like other languages. The last but not least point which this paper will discuss is that Ogihara (1995a)'s claim that the referential theory of tensed sentences is inadequate is untenable.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.373-375
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• 2021

국어의 경우 교착어이기 때문에 영어와 같이 어절 토큰화를 통하여 태깅할 경우 발전 가능성이 영어 보다 낮은 편이다. KoNLPy를 통해 형태소 단위로 분리하여 코퍼스를 토큰화한 형태를 그래프 데이터 베이스로 표현이 되지만 해당 모듈을 그래프 데이터베이스에서 코퍼스로 변환 시 음성파일의 완전 분리 및 실용성에 대한 검증이 필요하다. 본 논문에서는 Raspberry Pi에서 STT API를 활용한 형태소 표현을 나타내고 있다. 코퍼스로 변환된 음성 파일을 KoNLPy로 형태소 분석 후 태깅한다. 분석된 결과는 그래프 데이터베이스로 표현되며 형태소별로 나누어진 토큰으로 구분할 수 있음이 확인되었고, 실용성과 분리 정도를 판단하여 특정 목적성을 지닌 데이터 마이닝 추출이 가능한 것으로 판단된다.

• 인지과학
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• 제24권3호
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• pp.203-235
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• 2013

본 연구의 목적은 선행 연구에서 보고된 영어 모국어 아동의 굴절형태소 습득 과정을 대규모 언어습득 데이터베이스를 활용하여 검증하는 것이다. 이를 위해, 우리는 CHILDES(Child Language Data Exchange System) 데이터베이스에 등장하는 1-7세 영국 및 미국 아동 1,630명이 발화한 470만 어절 말뭉치를 대상으로 굴절형태소의 발달 과정을 분석하였다. 본 논문에서는 동사의 현재분사 -ing, 과거형 -(e)d, 형용사의 비교/최상급 -er/est 등의 형태소에 대해 어휘 유형(Type)과 사례(Token) 빈도, 전체 사례(Token)에 대한 유형(Type) 비율인 TTR(Type per Token Ratio), 어휘 다양성 척도인 Lexical Diversity(D) 값을 구하여 이를 국가 및 연령별로 비교, 분석하였다. 그 결과, 굴절형태소별로 연령과 D 값의 상관관계가 다르게 나타났다. 특히, 현재분사 -ing와 D 값 사이에는 주목할 만한 상관관계가 나타나지 않은 반면, 과거형 -(e)d의 경우 양의 상관관계 경향성이 보였고, 비교/최상급 -er/-est는 유의미한 상관관계를 보였다. 이는 현재진행형이 과거형보다 먼저 습득된다고 보고한 Brown(1973)의 견해를 지지한다. 다음으로, 과잉일반화에 따른 오류 표현이 2-3세 사이에 많이 나타나면서 U자형 발달 양상을 보였다. 과잉일반화도 현재분사보다 과거형에서 많이 나타났는데, 이것 또한 현재분사가 과거형보다 일찍 습득된다는 주장을 지지한다. 영국과 미국 아동의 연령별 굴절형태소 사용 양상을 비교한 결과, 미국 아동의 D 값이 영국 아동보다 높았다. 이는 미국 아동이 영국 아동보다 더 많은 어휘 유형에 대해 굴절형태소를 사용했음을 의미한다. 본 연구는 소수의 아동을 대상으로 수행된 선행 연구의 다양한 논점을 대규모 데이터베이스로 검증하고, CHILDES 코퍼스를 효율적으로 분석하는 연구 방법론을 제안했다는 점에서 의의가 있다.

• 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.

• International Journal of Internet, Broadcasting and Communication
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• 제14권2호
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• pp.55-62
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• 2022

A smart tourism chatbot is needed as a user interface to efficiently provide smart tourism services such as recommended travel products, tourist information, my travel itinerary, and tour guide service to tourists. We have been developed a smart tourism app and a smart tourism information system that provide smart tourism services to tourists. We also developed a smart tourism chatbot service consisting of khaiii morpheme analyzer, rule-based intention classification, and tourism information knowledge base using Neo4j graph database. In this paper, we develop the Korean and English smart tourism Name Entity (NE) datasets required for the development of the NER model using the pre-trained language models (PLMs) for the smart tourism chatbot system. We create the tourism information NER datasets by collecting source data through smart tourism app, visitJeju web of Jeju Tourism Organization (JTO), and web search, and preprocessing it using Korean and English tourism information Name Entity dictionaries. We perform training on the KoBERT-CRF NER model using the developed Korean and English tourism information NER datasets. The weight-averaged precision, recall, and f1 scores are 0.94, 0.92 and 0.94 on Korean and English tourism information NER datasets.

• 한국컴퓨터정보학회논문지
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• 제21권11호
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• pp.9-16
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• 2016

The central goal of the current paper is to investigate lexical transfer between Korean and English and to identify rule-governed behavior and to provide implications for development of computer-assisted translation(CAT) software for the two languages. It will be shown that Sankoff and Poplack's Free Morpheme Constraint can not account for all the range of data. A constraint is proposed that a set of case-assigners such as verbs, INFL, prepositions, and the possessive marker may not undergo lexical transfer. The translation software is also expected to be equipped with the proposed claim that English verbs are actually borrowed as nouns or as defective verbs to escape from the direct attachment of inflectional morphemes.

• Journal of Information Processing Systems
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• 제15권5호
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• pp.1119-1130
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• 2019

With the wide spread of Social Network Services (SNS), fake news-which is a way of disguising false information as legitimate media-has become a big social issue. This paper proposes a deep learning architecture for detecting fake news that is written in Korean. Previous works proposed appropriate fake news detection models for English, but Korean has two issues that cannot apply existing models: Korean can be expressed in shorter sentences than English even with the same meaning; therefore, it is difficult to operate a deep neural network because of the feature scarcity for deep learning. Difficulty in semantic analysis due to morpheme ambiguity. We worked to resolve these issues by implementing a system using various convolutional neural network-based deep learning architectures and "Fasttext" which is a word-embedding model learned by syllable unit. After training and testing its implementation, we could achieve meaningful accuracy for classification of the body and context discrepancies, but the accuracy was low for classification of the headline and body discrepancies.