• Information and Communications Magazine
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• v.34 no.6
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• pp.43-50
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• 2017

본고에서는 소셜 빅데이터에서 공공안전에 위협되고 사회적으로 이슈가 되는 재난사건을 추출하기 위한 방법으로 소셜 네트워크상에서 사용자 행동 분석과 시간분석을 반영한 토픽 모델링 기법을 알아본다. 소셜 사용자의 글 수, 리트윗 반응, 활동주기, 팔로워 수, 팔로잉 수 등 사용자의 행동 분석을 통하여 활동적이고 신뢰성 있는 사용자를 분류함으로써 트윗에서 스팸성과 광고성을 제외하고 이슈에 대해 신뢰성 높은 사용자가 쓴 트윗을 중요하게 반영한다. 또한, 트위터 데이터에서 새로운 이슈가 발생한 것을 탐지하기 위해 시간별 핵심어휘 빈도의 분포 변화를 측정하고, 이슈 트윗에 대해 감성 표현 분석을 통해 핵심이슈에 대해 사건 어휘를 추출한다. 소셜 빅데이터의 특성상 같은 날짜에 여러 이슈에 대한 트윗이 많이 생성될 수 있기 때문에, 트윗들을 토픽별로 그룹핑하는 것이 필요하므로, 최근 많이 사용되고 있는 LDA 토픽모델링 기법에 시간 특성과 사용자 특성을 분석한 시간상에서의 중요한 사건 어휘를 반영하고, 해당이슈에 대한 신뢰성 있는 사용자가 쓴 트윗을 중요시 반영하도록 토픽모델링 기법을 개선한 소셜 사건 탐지 방법에 대해 알아본다.

• Proceedings of the Korean Society for Information Management Conference
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• 2005.08a
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• pp.87-96
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• 2005

초등학생관련 자료의 유별 현황 및 어휘분석을 바탕으로 초등학교도서관을 위한 KDC 간략판을 개발하고자 시도되었다. 즉, 분류표의 수정 전개 범위는 최대한 KDC 4판의 기본 틀인 유, 강, 목을 그대로 유지하면서 자료의 유별 분포도를 분석하여 분류항목을 세분하였으며, 초등학생의 특성을 반영하기 위한 구체적인 방법으로 KDC 분류명사를 추출하여 초등학생을 대상으로 설문조사한 결과 및 초등학생관련 자료의 실증적인 어휘분석을 종합하여 분류항목의 수정전개에 반영하였다. 이 연구에서는 초등학교도서관을 대상으로 하였지만 중등학교도서관에 대해서도 이와 같은 실증적인 유별 현황 및 어휘분석 방법을 적용하여 주기적으로 분류표의 개정 작업에 반영한다면 KDC가 학교도서관을 위해 보다 실공적인 분류표가 될 것이다.

• Annual Conference on Human and Language Technology
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• 1999.10d
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• pp.117-122
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• 1999

본 연구는 형태소 분석에 필요한 언어 지식과 품사 태깅에 필요한 확률 정보를 별도의 언어 지식 추가 없이 학습 말뭉치를 통해서 얻어내는 방법을 제안한다. 먼저 품사 부착된 학습 말뭉치로부터 형태소 사전과 결합 정보를 추출한다. 그리고 자주 발생하는 어절 및 해석상 모호성이 많은 어절에 대해서는 학습 말뭉치에서 발견된 형태소 분석 결과를 저장하여 형태소 분석에 소요되는 시간과 형태소 분석의 정확률을 높인다. 또한 미등록어의 많은 부분을 차지하는 인명, 지명, 조직명에 대해서는 정보 추출 분야에서 사용하는 고유 명사 분류법으로 해결한다. 품사 태깅을 위해서는 품사열 정보와 품사열 정보로는 해결할 수 없는 경우를 위한 어휘 정보를 학습 말뭉치에서 추출한다. 품사열 정보와 어휘 정보는 정형화 과정을 거쳐 최대 엔트로피 모델의 자질로 사용되어 품사 태깅 시스템을 위한 확률 분포를 구성한다. 본 연구에서 제안하는 방법은 학습 말뭉치를 기반으로 한다는 특성에 의해 다양한 영역에 사용하기 쉽다. 또한 어휘 정보로 품사 문맥 정보를 보완하기 때문에 품사 분류 체계와 형태소 해석 규칙에 영향을 적게 받는다는 장점을 가진다. MATEC '99 데이터 실험 결과 형태소 단위로 94%의 재현률과 93%의 정확률을 얻을 수 있었다.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.30-35
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• 2008

The purpose of this study is to analyze and define user's emotional satisfaction factors to the PC OS GUI image. The study is to investigate the relationship between PC OS GUI Image and Sensitive Vocabula교 based on user's emotional preference. 47 user preferred sensitive words are collected by the initial survey. Through the similarity test, 47 words are narrowed down to 20 comprehend words. The semantic differential methods is used in the final survey with 5 step questionnaire. From this process, user preferred the GUI design that is vocabularized as Clear, Easy, Safety, Stability. Additionally, the result shows that the image of Clear is related to Safety and the image of Easy is related to Stability. The result of the study could be used in design PC OS GUI as base data.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.22 no.4
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• pp.28-34
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• 2004

사건 탐색 및 추적(TDT: Topic Detection and Tracking) 연구 [1]은 전세계 각 나라에서 매일 보도 되고 있는 신문이나 방송 뉴스 기사에서 "어떤 중요한 사건이 발생했는가\ulcorner"또는 "새로운 사건이 일어났는가\ulcorner"와 같이 그날 처음 발생한 사건을 탐색하거나, 같은 사건을 다루는 기사들을 탐색하거나, 예전에 발생한 사건과 관련된 사건인지를 추적해 나가는 것이다.된 사건인지를 추적해 나가는 것이다.

• Journal of Digital Contents Society
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• v.12 no.4
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• pp.541-550
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• 2011

MotionTypography is crucial to effective emotional communication in digital society. In this paper, I study movements to represent emotion using motiontypography and approach two goals: First to define an emotional measure by means of emotion assesses by the public, Second to research image characteristics corresponding to movements. In this dissertation, we collect emotional words by literature and experimental surveys and extract representative emotional words using KJ method and clustering analysis. The results of research, the emotional axes selected for motiontypography represent 'calm to active' and 'soft to stiff', the viewers feel a specific emotional state from some movements of motiontypography. If, we investigate the relationship of motiontypographic visual elements with emotional words are achieved together, I think it will serve as a motiontypographic guideline that enables helping the public to easily produce motiontypography.

• Design Convergence Study
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• v.14 no.4
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• pp.1-16
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• 2015

This study aims to understand distribution of the sentimental words on each genre and find relationship between box office performance and sentimental words in movie review using 673 movies that have more than 1,000 reviews. For the analysis, crawling movie reviews and made data was composed movie genre, movie name, sales, attendance, screen, normal attendance, 7 sentimental words. For analysis results, we used correlation analysis and Parallel coordinates. As a results, First, the highest box office value of the genre is comedy and the lowest box office value of the genre is horror through analyze box office on each genre. Secondly, Movie genre of fantasy feel a lot of boring emotion and Movie genre of SF feel a lot of anger emotion even if 'Happy' and 'Surprise' have highest sentiment value on every genre. Third, We found 'Anger' increase sentimental value when 'Disgust' increase sentimental value and 'Surprise' decrease sentimental value when 'Happy' increase sentimental value through analyze correlation relationship between sentimental words using total data. Fourth, We found 'Happy' have linear relationship between box office and 'Fear' have non-linear relationship between box office through analyze sentimental words according to box office performance.

• Cross-Cultural Studies
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• v.45
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• pp.195-218
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• 2016

This paper focuses on the terminology of the dictionary as an encyclopedic element in the Buddhist language. The previous study on Buddhist language can be divided into a philosophical approach to the language itself, a review of the linguistic perspective of a specific monk, and a linguistic examination of the Buddhist language. The linguistic examination of the Buddhist language is further divided into analysis of certain Buddhist scriptures, and a study of vocabulary used throughout the Buddhist sphere. The Buddhist vocabulary in the existing Korean dictionary is found in specialized areas such as name, place name, history, and Buddhism. By advancing the generalized words of the terminologies, the meanings of the terminologies and the general words are described as polysemy. It is possible to identify the degree of transition from terminology to general word depending on the distribution of senses. In the case of Buddhist vocabulary, the usage as a general language and as a Buddhist term was given priority, and vocabulary was also derived from a Buddhist term, although it was described as a general language. If a dictionary is changed according to the language unit it contains, the difference in a Buddhist terminology for each dictionary, and a conflict between the existing academic research result and the prior description, will need to be resolved through the collaboration of religious experts, linguists, and lexicographers.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.242-251
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• 2017

For the purposes of this research, a corpus of words was created from the English textbooks of the "First Middle School" for the gifted in North Korea, and using the corpus, their linguistic characteristics were analyzed. Although there have been many studies that identified the traits of English textbooks in the North Korea's general middle school, not much focus has been placed on the English textbooks used at North Korea's First Middle School. Initially, the structure of English textbooks of the first, second, fourth, and sixth grades that had been procured from the Information Center on North Korea was reviewed, after which their corpus was created. Then, by using Wordsmith Tools 7.0, linguistic properties and high frequency content words appeared in the English textbook of the first grade were analyzed specifically. Basic statistical data gathered indicated that while the number of vocabulary did not increase as students progress through the grades, the words used tended to diversify incrementally. In the mean time, a distribution of the high frequency content words by grade illustrated that a big difference was found between the content words used in the English texts of each grade, and it was a subject matter of the texts that determined such difference.

• Journal of Intelligence and Information Systems
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• v.15 no.3
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• pp.53-65
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• 2009

The part-of-speech determination is necessary for resolving the part-of-speech ambiguity in English-Korean machine translation. The part-of-speech ambiguity causes high parsing complexity and makes the accurate translation difficult. In order to solve the problem, the resolution of the part-of-speech ambiguity must be performed after the lexical analysis and before the parsing. This paper proposes the CatAmRes model, which resolves the part-of-speech ambiguity, and compares the performance with that of other part-of-speech tagging methods. CatAmRes model determines the part-of-speech using the probability distribution from Bayesian network training and the statistical information, which are based on the Penn Treebank corpus. The proposed CatAmRes model consists of Calculator and POSDeterminer. Calculator calculates the degree of appropriateness of the partof-speech, and POSDeterminer determines the part-of-speech of the word based on the calculated values. In the experiment, we measure the performance using sentences from WSJ, Brown, IBM corpus.