• 음성과학
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• 제15권1호
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• pp.7-23
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• 2008

This paper investigates tonal patterns of the prosodic constituents of an AP and a PWD in Korean and their relation with the morphological/syntactic structure. Specifically, this paper asks the following questions: First, if there are more than one PWD in an AP, how is each PWD specified in terms of tones? Secondly, in case that there is only one PWD in an AP that consists of several morphemes, is there any preference of the association between tones and the morphemes that constitute that PWD? Thirdly, if an AP dominates a PWD and if a PWD contains at least one morpheme of the lexical category, it follows that an AP should contain at least one morpheme of the lexical category. Can this be verified with the experimental data? In order to answer these questions, Experiment I and II were conducted with the target material consisting of a stem and suffixes that varied in length. The results of this preliminary test show that as the number of syllables in the target material increases, the more number of an AP tonal pattern occurs in it and as a result, in some cases, an AP consisting of suffixes only may occur.

• 한국콘텐츠학회논문지
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• 제19권1호
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• pp.548-558
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• 2019

인터넷 뉴스 댓글이 보편화 됨에 따라 악성 댓글이 확산되었고 이는 많은 사회 문제를 일으켜 왔다. 글은 심리 상태나 성격을 반영하기 때문에 악성 댓글을 분석하면 댓글을 작성할 때의 마음 상태를 추론할 수 있다. 본 연구에서는 영어권과 한국어권의 악성 댓글을 LIWC와 KLIWC를 사용하여 분석하였다. 그 결과, 영어와 한국어 공통으로 문장, 어절, 형태소, 문장 당 어절, 문장 당 형태소, 긍정적인 정서, 인지적 과정을 나타내는 단어가 악성 댓글이 일반 댓글보다 적게 사용되었으며, 3인칭 단수, 화, 정서적 과정을 나타내는 단어, 물리적 상태와 기능을 나타내는 단어, 속어가 악성 댓글이 일반 댓글보다 많이 사용되었다. 이는 악성 댓글을 작성할 때 사람들이 분노의 감정을 조절하지 못하고 충분히 생각하지 않은 상태에서 글을 작성하고 있음을 나타낸다. 따라서 댓글 작성 시, 작성 글을 모니터링 하도록 유도하거나 부정적 정서의 어휘가 많이 사용된 글을 다른 이용자에게 노출 시키지 않는 등의 방법을 인터넷 뉴스 서비스 제공자가 고려할 필요가 있다. 한편, 영어의 악성 댓글과 한글의 악성 댓글은 진정성 측면에서 차이가 발생했다. 좀 더 객관적 연구를 위해서 여러 시점의 댓글을 모집할 필요가 있다.

• 한국언어정보학회지:언어와정보
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• 제9권2호
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• pp.49-68
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• 2005

Application of chunking to English and some other European languages has shown that it is a viable parsing mechanism for natural languages. Although a small number of attempts have been made to apply chunking to the analysis of the Korean language, it still is not clear enough what criteria there are to identify appropriate units of chunking, and how efficient and valid the chunking algorithms would be when applied to some authentic Korean texts. The purpose of this research is to provide an alternative set of algorithms for chunking Korean, and to implement them, and to test them against some English-Korean parallel corpora, which is English and Korean bibles matched sentence by sentence. It is shown in the paper that aligning related texts and identifying matched phrases between the two languages can be achieved through appropriate chunking and matching algorithms defined on the morphologically-tagged parallel corpus. Chunking and matching processes are based on the content words rather than the function words, and the matching itself is done in terms of the transfer dictionary. The implementation is done in C and XML, and can be accessed through the Internet.

• 한국언어정보학회지:언어와정보
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• 제6권1호
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• pp.71-89
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• 2002

This paper proposes that concession should be analysed in terms of inferences based on the likelihood of event occurrence and that an alternative set of events should be presupposed in such inferences. In order to give an empirical content to this proposal this paper discusses the pragmatic aspects of the English word even and the Korean morpheme -lafo and claims that the notion of likelihood is the basis of the pragmatic inference of concession and the quasi-universal quantification erect. It is also claimed that unexpectedness, which is conceptually tied to concession, on the other hand, pertains to the same kind of pragmatic inference but presupposes the existence of an alternative set of individuals instead of an alternative set of situations.

• 정보처리학회논문지B
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• 제10B권1호
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• pp.47-56
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• 2003

한국어는 영어와 같이 공백을 단어의 경계로 사용하지만, 그 단어의 구조는 영어와 다소 차이가 있다. 영어는 일반적으로 공백 사이에 하나의 단어가 포함되나, 한국어는 여러 개의 단어 혹은 형태소가 포함된다. 이런 차이 때문에 일반적으로 한국어에서는 공백을 경계로 이루어진 단어를 어절이라고 한다. 본 논문에서는 하나의 어절 내에 포함된 단어들을 분리하고, 분리된 각 단어의 적절한 범주를 결정하는 방법을 제안한다. 본 논문에서는 사례기반 기계학습 방법을 이용하고 음절 단위로 단어를 분리한다. 사례기반 학습을 위해 사용된 자질집합은 이전 음절 자신의 음절, 이후의 두 음절, 자신의 음절에 대한 받침 정보, 이전 두 범주 정보이다. 제안된 시스템을 평가하기 위해서 ETRI 말뭉치와 KAIST 말뭉치를 사용하였으며, 두 말뭉치 모두에서 단어 분리의 F 측도가 97% 이상으로 비교적 좋은 성능을 보였다.

• 음성과학
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• 제5권2호
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• pp.77-91
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• 1999

The purpose of this paper is to investigate the phonetic characteristics of the 'focus' phrases associated with the particle '-man' in Korean. The particle '-man' is a bound morpheme which, like other postpositions such as the subject marker '-ka' and the object marker '-lil', the so-called 'case markers' in Korean, typically attaches to a noun (phrase). The semantics of '-man' roughly corresponds to that of only, its counterpart in English, and is thus classified as a 'delimiter' (Yang 1973). It is assumed in this paper that '-man', like only in English, should have a 'focus' associated with it (von Stechow 1991, Rooth 1992). In general, '-man' attached phrases get the focus, but sometimes the association is not clear-cut, especially in the cases of emphatic use of '-man' or when the context strongly favors other phrase as the focus (Choe 1996). In this paper, we compare the phonetic characteristics of the '-man' marked phrases with those to which '-ka'/'-lil' is attached, and conclude that the focused '-man' phrases show higher fundamental frequencies than their equally focused 'case' -marked counterparts. However, when the context clearly forces the focus to fall on phrases other than the '-man' or '-ka'/'-lil' attached ones, there is no meaningful difference in fundamental frequency between the '-man' and '-ka'/'-lil' attached phrases. We also compare the phonetic characteristics of the regular use of '-man' with those of the emphatic '-man'. According to our experiments, the emphatic '-man' does not bring forth its phonetic effects, namely, higher fundamental frequencies, on the' -man' attached words or phrases but rather in various other ways such as higher fundamental frequencies in '-man', lengthening of the following word-initial syllable, or the inclusion of the following word in the same accentual phrase. Finally, it is claimed that '-man' associated focus phenomena, especially the emphatic use of '-man', show some typical acoustic characteristics of the other well-known focus phenomena, namely, wh-interrogatives.

• 한국정보시스템학회지:정보시스템연구
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• 제30권1호
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• pp.65-84
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• 2021

Purpose Based on the development of artificial intelligence and big data technologies, the RegTech has been emerged to reduce regulatory costs and to enable efficient supervision by regulatory bodies. The word RegTech is a combination of regulation and technology, which means using the technological methods to facilitate the implementation of regulations and to make efficient surveillance and supervision of regulations. The purpose of this study is to describe the recent adoption of RegTech and to provide basic examples of applying RegTech to capital market regulations. Design/methodology/approach English-based ontology and deep learning technologies are quite developed in practice, and it will not be difficult to expand it to European or Latin American languages that are grammatically similar to English. However, it is not easy to use it in most Asian languages such as Korean, which have different grammatical rules. In addition, in the early stages of adoption, companies, financial institutions and regulators will not be familiar with this machine-based reporting system. There is a need to establish an ecosystem which facilitates the adoption of RegTech by consulting and supporting the stakeholders. In this paper, we provide a simple example that shows a procedure of applying RegTech to recognize and interpret Korean language-based capital market regulations. Specifically, we present the process of converting sentences in regulations into a meta-language through the morpheme analyses. We next conduct deep learning analyses to determine whether a regulatory sentence exists in each regulatory paragraph. Findings This study illustrates the applicability of RegTech-based ontology and deep learning technologies in Korean-based capital market regulations.

• 한국IT서비스학회지
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• 제15권3호
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• pp.115-125
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• 2016

Novels includes 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 kind of character names which have been created or will be created by authors. In addition, since Korean does not have capitalization feature, character names in Korean are harder to detect than those in English. Fortunately, however, Korean has postpositions, such as "-ege" and "hante", used by a sentient being or an animate object (noun). We call such postpositions as animate postpositions in this paper. In a previous study, the authors manually selected character names by referencing both Wikipedia and well-known people dictionaries after utilizing Korean morpheme analyzer, a proper noun dictionary, postpositions (e.g., "-ga", "-eun", "-neun", "-eui", and "-ege"), and titles (e.g., "buin"), in order to extract social networks from three novels translated into or written in Korean. But, the precision, recall, and F-measure rates of character identification are not presented in the study. In this paper, we evaluate the quantitative contribution of animate postpositions to character identification from novels, in terms of precision, recall, and F-measure. The results show that utilizing animate postpositions is a valuable and powerful tool in character identification without a proper noun dictionary from novels translated into or written in Korean.

• 한국IT서비스학회지
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• 제15권1호
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• pp.245-253
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• 2016

Background in a novel is most important elements with characters and events, and means time, place and situation that characters appeared. Among the background, spatial background can help conveys topic of a novel. So, it may be helpful for choosing a novel that readers want to read. In this paper, we are targeting Korean historical novels. In case of English text, It can be recognize spatial background easily because it use upper and lower case and words used with the spatial information such as Bank, University and City. But, in case Korean text, it is difficult to recognize that spatial background because there is few information about usage of letter. In the previous studies, they use machine learning or dictionaries and rules to recognize about spatial information in text such as news and text messages. In this paper, we build a nation dictionaries that refer to information such as 'Korean history' and 'Google maps.' We Also propose a method for recognizing spatial background based on patterns of postposition in Korean sentences comparing to previous works. We are grasp using of postposition with spatial background because Korean characteristics. And we propose a method based on result of morpheme analyze and frequency in a novel text for raising accuracy about recognizing spatial background. The recognized spatial background can help readers to grasp the atmosphere of a novel and to understand the events and atmosphere through recognition of the spatial background of the scene that characters appeared.

• 한국산학기술학회논문지
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• 제16권8호
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• pp.5565-5570
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• 2015

암묵인용문 인식은 학술문헌의 본문 텍스트 내에서 명시적 인용표지가 누락된 인용문장을 자동 인식하는 것으로 인용 기반 논문 검색 및 요약의 핵심 기술이다. 기존 암묵인용문 인식의 최신 연구들은 단어 ngram, 단서어구, 명시인용문과의 거리, 기존 연구자의 성, 기존 방법의 명칭 등 다양한 자질을 활용하여 50% 이상 인식 수준을 보고하고 있다. 그러나 대부분의 기존 연구들은 영어에 대해 수행되었으며 한국어의 경우 최근 긍정/부정 단서어구 패턴을 활용한 규칙 기반 시도에서 42% 성능 수준이 보고되어 있어 추가 성능 향상이 요구되는 상황이다. 이 연구에서는 한국어 어휘 자질을 사용하여 한국어 암묵인용문의 기계학습 기반 인식을 시도하였다. 이를 위해 어절, 형태소, 음절 단위에 기반한 다양한 크기의 어휘 ngram 자질들의 인식 성능을 비교 평가하고 한국어 암묵인용문 인식에 적합한 어휘 자질로 형태소 1gram 및 음절 2gram 단위를 결정하였다. 또한 이들 어휘 자질들을 전후 명시인용문들과의 인접성을 표현한 위치 자질들과 결합하여 한국어 암묵인용문 인식 성능을 50% 이상 수준으로 대폭 향상시켰다.