• Journal of Korean Home Economics Education Association
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• v.33 no.4
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• pp.1-13
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• 2021

The purpose of this study is to identify trends and potential themes of research on consumption of children and adolescents for 20 years by analyzing keywords. The keywords of 869 studies on consumption of children and adolescents published in journals listed in Korean Citation Index were analyzed using text mining techniques. The most frequent keywords were found in the order of youth, youth consumers, consumer education, conspicuous consumption, consumption behavior, and character. As a result of analyzing the frequency of keywords by dividing into five-year periods, it was confirmed that the frequency of consumer education was significantly higher betwn 2006 and 2010. Research on ethical consumption has been active since 2011, and research has been conducted on various topics instead of without a prominent keyword during the most recent 5-year period. Looking at the keywords based on the TF-IDF, the keywords related to the environment and the Internet were the main keywords between 2001 and 2005. From 2006 to 2010, the TF-IDF values of media use, advertisement education, and Internet items were high. From 2011 to 2015, fair trade, green growth, green consumption, North Korean defector youths, social media, and from 2016 to 2020, text mining, sustainable development education, maker education, and the 2015 revised curriculum appeared as important themes. As a result of topic modeling, eight topics were derived: consumer education, mass media/peer culture, rational consumption, Hallyu/cultural industry, consumer competency, economic education, teaching and learning method, and eco-friendly/ethical consumption. As a result of network analysis, it was found that conspicuous consumption and consumer education are important topics in consumption research of children and adolescents.

• Journal of the Korean earth science society
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• v.31 no.7
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• pp.785-797
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• 2010

This study identified the linguistic features of Earth science treatises through the analysis of the register. Data included three Korean treatises that were in geology, atmospheric science, and oceanography. The register of Earth science treatise was as follows: First, there were semantic, referential connections between Themes and Rhemes, that the messages and main points of the texts were expressed coherently and cohesively. Second, some predicates were used which were related to deductive inference, abductive inferences, or causal relation according to the genre elements of each text. The logical relations were not represented by the conjunctions but by the types of predicates. Third, most texts in the treatises showed interpersonally weak relationship using mental predicates related to possibilities, which meant scientists expressed indirectly their interpretation, explanation, or arguments. From these results, we argued that some activities of unpacking the language of science be included in science curriculum in order to improve students' literacy of science texts and understanding scientists' knowledge construction.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.619-630
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• 2015

The purpose of this study is to provide basic information to develop a game strategy plan of a team in a future by identifying the patterns of attack and pass of national men's professional volleyball teams and extracting core key words related with volleyball game performance to evaluate game performance using 'social network analysis' and 'text mining'. As for the analysis result of 'social network analysis' with the whole data, group '0' (6 players) and group '1' (11 players) were partitioned. A point of view the degree centrality and betweenness centrality in 'social network analysis' results, we can know that the group '1' more active game performance than the group '0'. The significant result for two group (win and loss) obtained by 'text mining' according to two groups ('0' and '1') obtained by 'social network analysis' showed significant difference (p-value: 0.001). As for clustering of each network, group '0' had the tendency to score points through set player D and E. In group '1', the player K had the tendency to fail if he attack through 'dig'; players C and D have a good performance through 'set' play.

• Science of Emotion and Sensibility
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• v.17 no.1
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• pp.71-78
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• 2014

We propose the sentiment pattern as a novel sentiment feature for more accurate text sentiment analysis, and introduce the rating inference of movie reviews using it. The text sentiment analysis is a task that recognizes and classifies sentiment of text whether it is positive or negative. For that purpose, the sentiment feature is used, which includes sentiment words and phrase pattern that have specific sentiment like positive or negative. The previous researches for the sentiment analysis, however, have a limit to understand accurately total sentiment of either a sentence or text because they consider the sentiment of sentiment words and phrase patterns independently. Therefore, we propose the sentiment pattern that is defined by arranging semantically all sentiment in a sentence, and use them as a new sentiment feature for the rating inference that is one of the detail subjects of the sentiment analysis. In order to verify the effect of proposed sentiment pattern, we conducted experiments of rating inference. Ratings of test reviews is inferred by using a probabilistic method with sentiment features including sentiment patterns extracted from training reviews. As a result, it is shown that the result of rating inference with sentiment patterns are more accurate than that without sentiment patterns.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.119-138
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• 2024

Text indicators are increasingly valuable in economic forecasting, but are often hindered by noise and high dimensionality. This study aims to explore post-processing techniques, specifically noise filtering and dimensionality reduction, to normalize text indicators and enhance their utility through empirical analysis. Predictive target variables for the empirical analysis include monthly leading index cyclical variations, BSI (business survey index) All industry sales performance, BSI All industry sales outlook, as well as quarterly real GDP SA (seasonally adjusted) growth rate and real GDP YoY (year-on-year) growth rate. This study explores the Hodrick and Prescott filter, which is widely used in econometrics for noise filtering, and employs sufficient dimension reduction, a nonparametric dimensionality reduction methodology, in conjunction with unstructured text data. The analysis results reveal that noise filtering of text indicators significantly improves predictive accuracy for both monthly and quarterly variables, particularly when the dataset is large. Moreover, this study demonstrated that applying dimensionality reduction further enhances predictive performance. These findings imply that post-processing techniques, such as noise filtering and dimensionality reduction, are crucial for enhancing the utility of text indicators and can contribute to improving the accuracy of economic forecasts.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.11a
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• pp.11-13
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• 2019

대중들에게 정보를 빠르고 정확하게 제공하는 대표 매체인 뉴스 기사는 일 평균 1만 5천 건 이상이 보도되고 있다. 특정 주제 또는 분야에 대한 전반적인 동향을 파악하고자 대량의 텍스트 데이터를 수집하여 텍스트 마이닝(Text mining)과 머신러닝 등을 적용하는 연구들이 활발하게 수행되고 있다. 본 연구에서는 서울시의 이슈 및 문제를 파악하고자 약 5년간 뉴스 기사를 수집하여 키워드 분석 및 토픽 모델링을 적용하였다. 분석 결과 5년간의 뉴스 기사에서 빈번하게 출현하는 키워드들을 도출하였고 연도별로 도출된 키워드들을 비교분석하였다. 또한 토픽 모델링 적용 결과 뉴스 기사를 구성하는 20개의 주제를 도출하였으며 이를 기반으로 서울시의 주요 이슈들을 파악할 수 있다. 본 연구는 연도별, 분야별 세부 내용 및 시계열 분석, 다른 도시들의 이슈 및 문제를 도출하는데 활용될 것으로 기대된다.

• Proceedings of the Korea Contents Association Conference
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• 2003.05a
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• pp.88-91
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• 2003

웹기반 교육은 사용자가 원하는 시간과 장소에서 학습자 스스로 수준별 학습이 .가능하며 능동적으로 학습에 참여할 수 있는 장점이 있다. 이를 바탕으로 한 웹 코스웨어는 원거리 학습자들의 학습 욕구를 가능케 했으며 기존의 텍스트, 사운드를 통한 단순한 콘텐츠에서 동영상 이미지를 중심으로 한 멀티미디어 동영상 강의, 하이퍼텍스트로 구성된 인터넷 홈페이지 등 주문형 교육 서비스(EOD : Education On Demand)가 가능해 졌다. 이처럼 현재 많은 분야에서 다양한 방법으로 웹기반 교육콘텐츠를 개발하여 학습에 활용하고 있다. 이에 본 연구에서는 양적으로 팽창하는 웹 코스웨어의 효율성을 분석하고 이를 통하여 보다 질적인 우수성을 포함하는 콘텐츠 활용 방안을 연구하고자 한다.

• Journal of Korean Library and Information Science Society
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• v.43 no.3
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• pp.313-332
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• 2012

This study looked at various definitions of reading and examined multiple aspects of reading from the perspective of related disciplines. The study also attempted to isolate specific factors of reading-author, reader, text, and context-and investigated the nature of each factor. The study focused on the communicational aspect of reading, especially on the interaction between the reader and the context.

• Annual Conference of KIPS
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• 2003.11b
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• pp.833-836
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• 2003

본 논문에서는 생물학적 문헌으로부터 유의미한 정보를 추출하는 바이오 텍스트 마이닝의 기본 단계인 생물학적 개체명 인식 모델을 제안하였다. 기존의 생물학적 개체명 인식은 규칙 혹은 코퍼스 구축뿐만 아니라 개체명 인식에 요구되는 기본 자원을 구축하는데만도 많은 시간과 비용이 요구되므로 한정된 도메인을 대상으로 연구가 진행되어 왔다. 본 논문에서 제안하는 개체명 인식 방법은 이러한 비용 문제 및 새로운 도메인으로의 이식성 문제를 극복하기 위해 UMLS 로부터 통계적인 방법으로 정보를 추출해 기본적인 언어자원을 구축하고 이를 이용해 규칙을 생성함으로써 개체명인식을 수행한다. 본 연구에서 제안하는 방법은 바이오 텍스트 마이닝 연구의 도메인 한정적인 문제를 해결하는데 기여할 수 있을 것으로 기대된다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10c
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• pp.544-546
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• 2003

인터넷의 급속한 발전으로 인해 네트워크를 통한 텍스트, 이미지. 사운드, 비디오 등과 같은 디지털 컨텐츠의 유통이 점차 대용량으로 변화하고 있다. 이러한 컨텐츠의 유통을 위해 쓰이는 URI는 텍스트의 한 페이지, 사운드 또는 비디오 클립, 정지 화상과 동영상은 물론 프로그램과 같은 컨텐츠를 인식하는데 쓰이고 URL을 이용하여 정보자원의 물리적 위치를 표시하는 문자열을 통해 정보자원에 접근하고 검색하게 된다. 하지만 휴대용 단말기를 이용하는 경우 단점이라 할 수 있는 입력기능의 제한으로 인해 정보이용이 쉽지 않기 때문에 정보 접근을 위한 새로운 URI 체계와 서비스 환경이 필요하다. 새로운 URI 체계에 하나의 대안으로 바코드나 특정 이미지와 같은 화상을 이용할 수 있는 방법이 있으며 이를 화상 URI로 체계화시키는 작업이 필요하다. 본 논문에서는 관련 기술들을 연구하고 화상 URI 시스템에서 사용되어질 URI 체계를 현재 세계 표준으로 유력한 DOI를 따르는 네임스페이스 구성에 관하여 연구하고 서비스 제공을 위해 구축되어져야할 환경에 관해 기술한다.