• 한국의류학회지
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• 제46권6호
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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.

• 말소리와 음성과학
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• 제7권1호
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• pp.117-124
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• 2015

This paper investigates the acoustic characteristics of English fricatives in the TIMIT corpus, with a special focus on the role of gender in rendering fricatives in American English. The TIMIT database includes 630 talkers and 2342 different sentences, comprising over five hours of speech. Acoustic analyses are conducted in the domain of spectral and temporal properties by treating gender as an independent factor. The results of acoustic analyses revealed that the most acoustic properties of voiceless sibilants turned out to be different between male and female speakers, but those of voiceless non-sibilants did not show differences. A classification experiment using linear discriminant analysis (LDA) revealed that 85.73% of voiceless fricatives are correctly classified. The sibilants are 88.61% correctly classified, whereas the non-sibilants are only 57.91% correctly classified. The majority of the errors are from the misclassification of /ɵ/ as [f]. The average accuracy of gender classification is 77.67%. Most of the inaccuracy results are from the classification of female speakers in non-sibilants. The results are accounted for by resorting to biological differences as well as macro-social factors. The paper contributes to the understanding of the role of gender in a large-scale speech corpus.

• 한국수정란이식학회지
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• 제26권1호
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• pp.57-63
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• 2011

This study was performed to the expressions of pregnancy-associated plasma protein-A (PAPP-A) and 20alpha-hydroxysteroid dehydrogenase ($20{\alpha}$-HSD) in bovine corpus luteum during early pregnancy. To determine the function of PAPP-A gene during early pregnancy, we collected corpus luteum samples on 30, 60 and 90 days of pregnancy in bovine. The mRNA expression of PAPP-A, $20{\alpha}$-HSD, progesterone-receptor (PR) and insulin-like growth factor binding protein4 (IGFBP4) gene was conducted by Real-time PCR. In parallel with mRNA levels, The protein expressions of PAPP-A and $20{\alpha}$-HSD were detected by immunological analysis. The mRNA expressions $20{\alpha}$-HSD and PAPP-A significantly increased on day 90 in the corpus luteum during pregnancy. The mRNA expression of PR and JGFBP4 in the corpus luteum progressively was enhanced at 30 to 60 day, but decreased on 90 day of pregnancy in the corpus luteum. The expression patterns of these genes, PAPP-A and $20{\alpha}$-HSD were similar pattern in these tissues. In conclusion, PAPP-A and $20{\alpha}$-HSD activity in corpus luteum could be played a role for early pregnancy manifestation.

• 영어어문교육
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• 제16권4호
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• pp.91-106
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• 2010

This study examines the use of hedges in cross-cultural communication between EFL learners in an e-learning environment. The study analyzes the use of hedges in a corpus of an interactive web with a bulletin board system through which college students of English at Japanese and Korean universities interacted with each other discussing the topics of local and global issues. It compares the use of hedges in the students' corpus to that of a native English speakers' corpus. The result shows that EFL learners tend to use relatively smaller number of hedges than the native speakers in terms of the frequencies of the total tokens. It further reveals that the learners' overuse of a single versatile high-frequency hedging item, I think, results in relative underuse of other hedging devices. This indicates that due to their small repertoire of hedges, EFL learners' overuse of a limited number of hedging items may cause their speech or writing to become less competent. Based on the result and interviews with the learners, the study also argues that hedging should be understood in its social contexts and should not be understood just as a lack of conviction or a mark of low proficiency. Suggestions were made for using computer corpora in understanding EFL learners' language difficulties and helping them develop communicative and pragmatic competence.

• 말소리와 음성과학
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• 제8권3호
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• pp.1-9
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• 2016

This paper investigated the phoneme distribution and phonological processes of orthographic and pronounced phrasal words in light of syllable structure in the Seoul Corpus in order to provide linguists and phoneticians with a clearer understanding of the Korean language system. To achieve the goal, the phrasal words were extracted from the transcribed label scripts of the Seoul Corpus using Praat. Following this, the onsets, peaks, codas and syllable types of the phrasal words were analyzed using an R script. Results revealed that k0 was most frequently used as an onset in both orthographic and pronounced phrasal words. Also, aa was the most favored vowel in the Korean syllable peak with fewer phonological processes in its pronounced form. The total proportion of all diphthongs according to the frequency of the peaks in the orthographic phrasal words was 8.8%, which was almost double those found in the pronounced phrasal words. For the codas, nn accounted for 34.4% of the total pronounced phrasal words and was the varied form. From syllable type classification of the Corpus, CV appeared to be the most frequent type followed by CVC, V, and VC from the orthographic forms. Overall, the onsets were more prevalent in the pronunciation more than the codas. From the results, this paper concluded that an analysis of phoneme distribution and phonological processes in light of syllable structure can contribute greatly to the understanding of the phonology of spoken Korean.

• 정보과학회 논문지
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• 제41권9호
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• pp.642-651
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• 2014

본 논문에서는 음절 단위의 한국어 형태소 분석 방법에 적용할 수 있는 세 가지 확률 모델을 제안하고, 품사 태깅 말뭉치를 이용하여 각 확률 모델의 성능을 평가한다. 성능 평가를 위해 1,000만 어절 규모의 세종 말뭉치를 10 개의 세트로 나누고 10 배수 교차 검증 결과 98.4%의 정답 제시율을 얻을 수 있었다. 제안된 확률 모델은 각 음절에 대하여 품사 태그를 먼저 부착한 후 원형 복원 및 형태소 생성을 하기 때문에 원형 복원을 먼저 하는 기존 확률 모델에 비하여 탐색 공간이 크게 줄어들어 형태소 분석 과정이 훨씬 간결하고 효율적이어서 분석 속도가 기존의 초당 수 백 어절에서 14만 7천 어절로 약 174배 가량 향상시킬 수 있었다.

• ETRI Journal
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• 제35권5호
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• pp.838-848
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• 2013

This paper presents a novel approach to automatically generate Korean multiword sentiment expressions by using a seed sentiment lexicon and a large-scale domain-specific corpus. A multiword sentiment expression consists of a seed sentiment word and its contextual words occurring adjacent to the seed word. The multiword sentiment expressions that are the focus of our study have a different polarity from that of the seed sentiment word. The automatically extracted multiword sentiment expressions show that 1) the contextual words should be defined as a part of a multiword sentiment expression in addition to their corresponding seed sentiment word, 2) the identified multiword sentiment expressions contain various indicators for polarity shift that have rarely been recognized before, and 3) the newly recognized shifters contribute to assigning a more accurate polarity value. The empirical result shows that the proposed approach achieves improved performance of the sentiment analysis system that uses an automatically generated lexicon.

• 한국멀티미디어학회논문지
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• 제23권4호
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• pp.595-602
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• 2020

We propose a generative probabilistic model with Dirichlet prior distribution for topic modeling and text similarity analysis. It assigns a topic and calculates text correlation between documents within a corpus. It also provides posterior probabilities that are assigned to each topic of a document based on the prior distribution in the corpus. We then present a Gibbs sampling algorithm for inference about the posterior distribution and compute text correlation among 50 abstracts from the papers published by IEEE. We also conduct a supervised learning to set a benchmark that justifies the performance of the LDA (Latent Dirichlet Allocation). The experiments show that the accuracy for topic assignment to a certain document is 76% for LDA. The results for supervised learning show the accuracy of 61%, the precision of 93% and the f1-score of 96%. A discussion for experimental results indicates a thorough justification based on probabilities, distributions, evaluation metrics and correlation coefficients with respect to topic assignment.

• 중국학논총
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• 제62호
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• pp.49-69
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• 2019

This study refers to the methodology of study of usage patterns by dissolving the study of Korean auxiliary particle '만, 밖에, 뿐' and Chinese range adverb '只, 光, 僅', and uses the actual language data of Korean native speakers and Chinese native speakers Using the constructed corpus, we looked at the usage patterns of auxiliary particles '만, 밖에, 뿐' and range adverb '只, 光, 僅' respectively. In the Korean and Chinese corpora, the Korean auxiliary particle '만, 밖에, 뿐' and Chinese range adverb '只, 光, 僅' are each 300 sentences, and a total of 1800 are used as analytical corpus. through the analysis of the examples, the features and differences such as the appearance ratio of Korean and Chinese, appearance environment are revealed. the analysis results of Korean and Chinese are compared to find common points and differences.

• 한국콘텐츠학회논문지
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• 제21권1호
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• pp.333-342
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• 2021

본 연구에서는 대표적인 영미 아동 모험 소설 『보물섬』의 언어적 특징을 파악하기 위해 『보물섬』을 코퍼스화 하여 어휘, 리마, 키워드, n-그램을 분석하였다. 이 연구를 통해 고빈도 어휘가 텍스트의 핵심어라는 일반적인 주장과 달리 『보물섬』의 고빈도 어휘는 『보물섬』과 직접 관련이 없는 기능어, 고유명사 등이 최상위층에 포진하고 있다는 것을 발견하였고, 통계적인 방법으로 추출한 『보물섬』 키워드 역시 『보물섬』의 내용을 가늠하기에 충분하지 않음을 발견하였다. 따라서 1차 정량적인 키워드 분석 후 진행된 2차 정성적인 키워드 분석을 통해 추출한 30개의 핵심 키워드를 통해 『보물섬』 내용을 신속하고 구체적으로 파악하는 단초를 마련하였고, 이를 바탕으로 그동안 직관적으로만 회자 되던 『보물섬』에 나타난 남성성을 계량적으로 분석할 수 있었다. 또한, n-그램 분석을 통해 『보물섬』의 작가가 다른 작가에 비해 선호하고 자주 사용하는 연속어휘구를 발견하였고, 이를 토대로 문학 작품의 계량적 연구가 가능한 코퍼스 문체론 연구의 가능성을 탐색하였다. 본 연구를 통해 밝혀낸 연구결과가 영미 아동문학 콘텐츠의 확산과 코퍼스 문체론 연구에 도움이 되기를 희망한다.