• 한국언어정보학회지:언어와정보
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• 제7권1호
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• pp.23-40
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• 2003

In this paper, we have proposed Auto-TUS, an automatic transcription module of three union symbols-hyphen, dash and tilde (‘­’, ‘―’, ‘∼’)-using their linguistic contexts. Few previous studies have discussed the problems of ambiguities in transcribing symbols into Korean alphabetic letters. We have classified six different reading formulae of the union symbols, analyzed the left and right contexts of the symbols, and investigated selection rules and distributions between the symbols and their contexts. Based on these linguistic features, 86 stereotyped patterns, 78 rules and 8 heuristics determining the types of reading formulae are suggested for Auto-TUS. This module works modularly in three steps. The pilot test was conducted with three test suites, which contains respectively 418, 987 and 1,014 clusters of words containing a union symbol. Encouraging results of 97.36%, 98.48%, 96.55% accuracy were obtained for three test suites. Our next phases are to develop a guessing routine for unknown contexts of the union symbols by using statistical information; to refine the proper nouns and terminology detecting module; and to apply Auto-TUS on a larger scale.

• 영어어문교육
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• 제4호
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• pp.179-206
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• 1998

Despite the fact that the phenomenal success of the classical model in phonology in terms of a small set of binary atomic primitives has encouraged the use of criterical features in the characterization of syntactic and semantic categories, cognitive linguists have recently found many evidences against it and proposed a valid alternative like prototype approach to classical model of linguistic categorization. In this paper the examples with prototype effects are shown in phonology, morphology, and syntax. In phonology there is no clear-cut borderline in initial sounds such as / r, m, n, v, ${\eth}$, z, w. j, b. d, g / and between vowels and consonants. In morphology family resemblance is shown between strong verbs and past tenses. In syntax there is no borderline among various kinds of sentences such as declarative, command, WH-question, yes-no question, etc.

• The Journal of the Acoustical Society of Korea
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• 제16권1E호
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• pp.64-74
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• 1997

In many decision making systems, rule-based approaches are used to solve complex problems in the areas of pattern analysis and computer vision. In this paper, we present methods for generating fuzzy IF-THEN rules automatically from training data for pattern classification and high-level computer vision. The rules are generated by construction minimal approximate fuzzy aggregation networks and then training the networks using gradient descent methods. The training data that represent features are treated as linguistic variables that appear in the antecedent clauses of the rules. Methods to generate the corresponding linguistic labels(values) and their membership functions are presented. In addition, an inference procedure is employed to deduce conclusions from information presented to our rule-base. Two experimental results involving synthetic and real are given.

• 비교문화연구
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• 제32권
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• pp.5-28
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• 2013

In this paper, a style-based approach to translating literary texts is introduced and used. The aim of the study is to work out a stylistic approach to translating literary texts from Arabic into English. The approach proposed in the current study is a combination of four major stylistic approaches, namely linguistic stylistics, literary stylistics, affective stylistics and cognitive stylistics. It has been shown from data analysis that by adopting a style-based approach that can draw from the four stylistic approaches, translators, as special text readers, can easily derive a better understanding and appreciation of texts, in particular literary texts. Further, it has been shown that stylistics as an approach is objective in terms of drawing evidence from the text to support the argument for the important stylistic features and their functions. However, it loses some of its objectivity and becomes dependent and subjective.

• 이베로아메리카
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• 제16권2호
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• pp.151-188
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• 2014

This work aims to describe pragmatic strategies and linguistic features of replies that occur in the comment section of online newspapers. The dominant media in this digital age is the Internet and its rapid development and expansion of use have contributed not only to the change of the form of production of journalistic texts, but also to the consumption of those texts. In the past, the news was transmitted in a unidirectional way but now readers of online newspapers do not remain passively reading the articles. They actively participate in the exchange of opinions with other readers. The individual consumption of journalistic texts has become a collective and social act. The purpose of the study is to investigate the communication intention of the users of comment sections and analyze the linguistic formulation of replies. We attempt to discover specific aspects of replies and responses for online newspaper articles, considering them as an independent type of Computer Mediated Communication (Internet Mediated Communication). Observing language attitudes appearing in the electronic environment and discovering the characteristics of the Spanish language on the Internet will allow us to contribute to understand the theoretical aspects related to the CMO better.

• 정보처리학회논문지B
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• 제17B권1호
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• pp.93-98
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• 2010

본 논문에서는 폭발적으로 증가하고 있는 상품평을 효과적으로 활용하기 위해 언어적 분석을 통하여 상품 평가를 요약하는 시스템을 제안한다. 시스템에서는 스커트 상품 분류의 경우 '디자인'과 '재질'과 같이, 상품을 평가하는 기준이 되는 항목에 대한 상품평의 부정과 긍정의 극성 여부를 판별하여 그래프 형태로 요약하여 제시한다. 본 논문에서는 작은 시드 어휘와 문맥에 기반한 자동 확장 방법을 사용하여 평가 항목 별 평가 어휘 극성 사전을 구축하여 평가 항목에 대한 상품평의 극성을 판정한다. 제안한 방식은 여러 온라인 쇼핑몰의 실제 상품평에 대한 실험에서 극성 사전 추출에서 평균 69.8%의 정확율과 문장별 극성 식별에서 평균 81.8%의 정확율을 보였다.

• 한국산학기술학회논문지
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• 제11권8호
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• pp.3021-3027
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• 2010

예제 기반 챗봇은 사용자 발화와 가장 유사한 예제 발화를 대화 예제 데이터베이스로부터 검색하여 응답을 생성한다. 가장 유사한 발화를 찾는 것은 응답의 적절성과 직결되는 것임에도 불구하고, 유사 발화 검색을 위해 어떠한 자질을 사용할 것인지, 어떠한 방식이 좋은 지에 대한 기존 연구는 부족하였다. 본 연구에서는 검색의 정확도와 예제의 활용도를 높이기 위해 다양한 어휘적, 의미적 자질을 이용한 기계 학습 방법을 제안한다. 실험 결과 1) 대화 예제 데이터베이스의 활용도 2) 예제 발화의 매칭의 정확률 3) 답변의 질적인 측면에서 제안하는 방법은 기존의 방법에 비해 더 나은 성능을 보였다.

• 아시아태평양코퍼스연구
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• 제2권1호
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• pp.35-45
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• 2021

With the wide spread of the Common European Framework of Reference (CEFR) scales, many studies attempt to apply them in routine teaching and rater training, while more evidence regarding criterial features at different CEFR levels are still urgently needed. The current study aims to explore complexity features that distinguish and predict CEFR proficiency levels in oral performance. Using a quantitative/corpus-based approach, this research analyzed lexical and syntactic complexity features over 80 transcriptions (includes A1, A2, B1 CEFR levels, and native speakers), based on an interview test, Standard Speaking Test (SST). ANOVA and correlation analysis were conducted to exclude insignificant complexity indices before the discriminant analysis. In the result, distinctive differences in complexity between CEFR speaking levels were observed, and with a combination of six major complexity features as predictors, 78.8% of the oral transcriptions were classified into the appropriate CEFR proficiency levels. It further confirms the possibility of predicting CEFR level of L2 learners based on their objective linguistic features. This study can be helpful as an empirical reference in language pedagogy, especially for L2 learners' self-assessment and teachers' prediction of students' proficiency levels. Also, it offers implications for the validation of the rating criteria, and improvement of rating system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권10호
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• pp.3390-3405
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• 2022

Long Short-Term Memory (LSTM) combined with attention mechanism is extensively used to generate semantic sentences of images in image captioning models. However, features of salient regions and spatial information are not utilized sufficiently in most related works. Meanwhile, the LSTM also suffers from the problem of underutilized information in a single time step. In the paper, two innovative approaches are proposed to solve these problems. First, the Synergy-Gated Attention (SGA) method is proposed, which can process the spatial features and the salient region features of given images simultaneously. SGA establishes a gated mechanism through the global features to guide the interaction of information between these two features. Then, the Recurrent Fusion LSTM (RF-LSTM) mechanism is proposed, which can predict the next hidden vectors in one time step and improve linguistic coherence by fusing future information. Experimental results on the benchmark dataset of MSCOCO show that compared with the state-of-the-art methods, the proposed method can improve the performance of image captioning model, and achieve competitive performance on multiple evaluation indicators.

• 한국과학교육학회지
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• 제41권2호
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• pp.71-82
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• 2021

교과서를 통한 학습의 효율성을 최대화하기 위해서는 교과서에 수록된 텍스트 특성이 예상된 학습자의 특성(i.e., 언어적 및 인지적 능력, 배경지식 수준)에 따라 체계적으로 조절되어야 한다. 이에 따라 현재 연구에서는 과학교과서 개발에 이러한 체계적인 원칙이 반영되어 있는지를 알아보기 위하여 중학교 1, 2, 3학년 과학교과서의 학년 간 언어적 특성을 비교 분석하였다. 구체적으로 한국어 분석 프로그램인 Auto-Kohesion 시스템을 활용하여 기존 텍스트 분석 연구에 많이 활용되었던 텍스트 표층 구조 측정치, 어휘 관련 측정치, 통사적 복잡성 측정치와 같은 피상적 측정치에 더하여 여러 정합성 관련 측정치(e.g., 명사 반복, 접속사, 대명사)를 분석하였다. 주요 분석 결과, 대체로 어절 및 문장 길이, 어휘 빈도와 같은 피상적으로 두드러지는 특성에 대해서는 학년이 증가함에 따라 텍스트 복잡도가 상승하는 방향으로 단계적으로 조절이 이루어졌지만, 그 외의 많은 언어적 특질에 대해서는 체계적으로 조절되지 않은 것으로 나타났다. 특히 여러 정합성 측정치들이 교과서 개발 과정에서 충분히 고려되지 않은 것으로 시사되었다. 이러한 결과는 저학년 학습자들이 교과서를 사용할 때 발달 단계에 맞지 않는 어려운 텍스트를 접할 가능성이 있어서 학습 의욕 및 효율성 저하 현상이 발생할 수 있다는 것을 제시한다. 아울러 고학년 교과서가 고등 교육을 대비하여 더욱 복잡한 텍스트를 처리할 수 있는 능력을 개발시키기 위한 용도로 적절하지 않을 수 있음을 시사한다. 본 연구는, 추후 교과서 개발 과정에서, 예상된 독자 특성의 변화에 따라 정합성 측정치를 포함한 여러 언어적 특성이 단계적으로 조절되어야 함을 제안한다.