• Proceedings of the Korea Contents Association Conference
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• 2017.05a
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• pp.139-140
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• 2017

본 연구는 공과대학 학생들이 배우는 전공영어로서의 특수목적영어(ESP)에 대해 코퍼스 기반 접근법의 유용성을 논하고자 한다. 이에 본 연구에서는 공과대학에서 사용하는 전공텍스트를 코퍼스로 구축하여 컴퓨터에 기반한 분석에서 나온 결과들을 제시하면서 공학영어 코퍼스의 특성을 살펴보고 궁극적으로 영어매개수업을 듣는 공대학생들의 데이터 기반 학습에 일조하고자 한다. 본 연구에서 사용된 목표 코퍼스는 세부전공과 상관없이 공통적으로 적용되는 공학과목을 선정하여 구축되었고 비교대상인 참조 코퍼스는 British National Corpus를 사용하였다. 공학영어 코퍼스는 총 단어 180만개, 단어 유형 만 6천여개로 이루어졌고 코퍼스 분석도구인 AntConc 3.4.4를 이용하여 빈도 분석과 키워드 분석이 수행되었다. 고빈도수 어휘의 분석결과 목표 코퍼스와 참조 코퍼스에서 가장 빈번하게 나타나는 어휘군은 내용어(content words)보다는 기능어(function words) 형태가 많다는 점이 나타났고 내용어군만 분석결과 참조코퍼스에 비해 공학영어 코퍼스에 과학영역의 변이어가 많이 분포하고 있음이 드러났다. 또한 키워드 분석에서는 공학영어 코퍼스의 키워드 동사군이 전문적인 어휘(technical vocabulary)보다는 비전문적인 학술적 어휘(non-technical academic vocabulary)가 상대적으로 많이 분포되어 있음이 드러나 ESP교육을 실시함에 있어서 전공관련 전문영어와 함께 일반적인 학술 영어에 대한 인식을 고양해야 할 필요성이 대두된다.

• Journal of the Korean Society for Library and Information Science
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• v.17
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• pp.339-366
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• 1989

Appearance of full-text online is the most encouraging phenomenon ·during the development of databases. The full-text databases of today is derived from by-product of electronic publication of printed materials. Now, there are also some movements toward electronic production of documents in Korea although not powerful. The present study is designed to examine the characteristics and effective retrieval method of full-text databases now commercially available through various vendors. The outline of this paper IS as follows: First, background and present situation of existing full-text database services through national and worldwide are examined. Second, free-text searching system of full-text databases is compared with controlled vocabulary system. The factors influencing on free-text retrieval performance, searching thesaurus, and hybrid or compromising system, which is using limited controlled vocabulary in conjunction with natural language for the enrichment needed for practical operation of the . system, are examined. Third, user demands through the analysis of preceding studies on 'various types of full-text databases are recognised. Fouth, application of CD-ROM full-text database to the libraries and information centers is examined as prospective resources for them. Finally, some problems and prospect of full-text databases are presented.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.9
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• pp.1483-1494
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• 2009

This study analyzes the locution of television home shopping show hosts for apparel products with a focus on the selling points and vocabulary use. A qualitative content analysis was conducted for 15 recorded home shopping shows selling women's overcoats and jackets. The results are as follows. First, 8 dimensions of selling points were revealed: Promotions, brand popularities, the experiences of shopping hosts, fashion trend information, conformity motivation and suggestion, intangible attributes, tangible attributes, and compared/leading differences. The most frequent selling point was tangible attributes. Following this were, promotions, conformity motivation and suggestion, compared/leading differences, intangible attributes, brand popularity, the experiences of the shopping hosts, and fashion trend information in order. The selling points were almost proper to decrease the perceived risks of home shopping consumers. Second, shopping hosts frequently used the clothing terms without any expatiations and used loan words (foreign language terms) instead of the direct Korean translations. In the conclusion, the development of a marketing strategy focusing on shopping host management is suggested.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.786-789
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• 2004

For the accurate evaluation of traffic noise with various spectrums and fluctuation characteristics, evaluation systems should reflect not only physical quantities but also the psychological respects of individual persons. In this study, adequate words for evaluating traffic noise have been extracted by reviewing the existing vocabularies and augmenting this with the results of a questionnaire prepared especially for apartment dwellers. As a result of this study, followings are suggested. 1) Vocabularies such as 'disagreeable', 'annoying', 'strident', 'disturbed', 'irritate', 'unpleasant', 'dislike' are classified into the first factor by factor analysis. 2) As a result of surveying overlapping vocabularies for each sound sources, 'noisy', 'annoying', strident', 'unpleasant', 'loudness' are main unpleasant vocabularies to franc noise occurring in our domestic apartment houses.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.59-65
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• 2021

This is a case study on the use of Albert Camus' La Peste, which has gained its popularity in today's generation of post-COVID as well as the use of big data analysis tools for major and elective classes. First, we asked students majoring in French to compare the use of vocabulary and the number of appearances for characters using big data analysis, for about 400 pages of the original text. As a result, we were able to confirm a similar relationship between Camus' Absurdism and the vocabulary used within La Peste, in addition to noting the heavy frequency of resistant characters. Students in elective classes were asked to read the literature in a Korean-translated version to determine the frequency of vocabulary and characters' appearances. Students were able to strongly relate to La Peste due to its commonality between COVID and the plague in the literature. We also received high levels of class satisfaction regarding the use of big data analysis tools. The students showed a positive response both towards choosing La Peste as the work of literature and using big data, the main tool in the Fourth Industrial Evolution. We were able to identify good results even in a non-contact environment, as long as the literature does not rely on traditional methods but rather lectures to reflect current situations.

• Journal of Korean language education
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• v.28 no.3
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• pp.53-83
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• 2017

The goal of this study is to examine whether the genre characteristics of newspaper articles are appropriately reflected in Korean language textbooks. For the purpose of this study, two corpora were built with 17 textbook articles and 60 newspaper articles respectively. The average sentence length and frequency of vocabulary in each corpus were measured. It was found that the sentences of articles in textbooks tended to have longer sentence length and more complicated structures than the articles in newspapers. For instance, sentences in the textbook articles had more verbal endings, such as conjunctive and transforming endings. On the other hand, in case of vocabulary representing 'timeliness', there was a high frequency of adverbs and nouns which were related to year, month, and time in actual articles, while it is found to be very limited in textbooks. Also, typical translative styles such as '-ko itta', '-e ttareumyun' were more prominent in textbooks than in newspaper articles. In the case of abbreviated and omitted form of particles, this was a characteristic that appeared only in actual articles because of the constraint of space. It is significant that this paper offers suggestions for the development of reading materials for Korean language education by revealing that the genre typology of actual newspaper articles is not adequately reflected in current textbooks.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.6
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• pp.1142-1160
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• 2022

Text data plays a significant role in understanding and analyzing trends in consumer, business, and social sectors. For text analysis, there must be a corpus that reflects specific domain knowledge. However, in the field of fashion, the professional corpus is insufficient. This study aims to develop a taxonomy and thesaurus that considers the specialty of fashion products. To this end, about 100,000 fashion vocabulary terms were collected by crawling text data from WSGN, Pantone, and online platforms; text subsequently was extracted through preprocessing with Python. The taxonomy was composed of items, silhouettes, details, styles, colors, textiles, and patterns/prints, which are seven attributes of clothes. The corpus was completed through processing synonyms of terms from fashion books such as dictionaries. Finally, 10,294 vocabulary words, including 1,956 standard Korean words, were classified in the taxonomy. All data was then developed into a web dictionary system. Quantitative and qualitative performance tests of the results were conducted through expert reviews. The performance of the thesaurus also was verified by comparing the results of text mining analysis through the previously developed corpus. This study contributes to achieving a text data standard and enables meaningful results of text mining analysis in the fashion field.

• Proceedings of the Acoustical Society of Korea Conference
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• 1993.06a
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• pp.121-124
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• 1993

This paper is a study on the word recognition using neural network. A limited vocabulary, speaker independent, isolated word recognition system has been built. This system recognizes isolated word without performing segmentation, phoneme identification, or dynamic time wrapping. It needs a static pattern approach to recognize a spatio-temporal pattern. The preprocessing only includes preceding and tailing silence removal, and word length determination. A LPC analysis is performed on each of 24 equally spaced frames. The PARCOR coefficients plus 3 other features from each frame is extracted. In order to simplify a structure of neural network, we composed binary code form to decrease output nodes.

• Journal of The Korean Digital Architecture Interior Association
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• v.3 no.2
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• pp.14-19
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• 2003

In this paper, I tried to apply the viewpoint and the method of "Cultural Study" to the analysis of a Architecture. "SE HAN DO(歲寒圖/ Jeonghee Kim 金正喜/ 1844)", the masterpiece of the "literary artist's paintings"(文人畵) is used as a 'TEXT‘(: parole) and analysed to show how artist's value and social-cultural ideology (as a 'CONTEXT':langue) are projected to the space and architectural vocabulary.

• Journal of Information Technology Services
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• v.12 no.4
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• pp.423-434
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• 2013

Since acquiring intelligence about political situations around the Korea Peninsular in a direct manner is nearly impossible, it is inevitable for the individuals or companies to rely on open and indirect data such as newspapers. However, since the contents in the newspapers are substantially unstructured and very large, conventional content analysis is time-consuming and hence very costly. Hence, this paper aims to propose a sentimental analysis method which computes daily 'peace index' from unstructured data in the newspapers. From the content analysis, words and phrases which represent the sentiment of a nation are carefully identified. To show the feasibility of the idea proposed in this paper, a prototype system with vocabulary repository about political situations was developed for estimating peace index automatically.