• 한국초등과학교육학회지:초등과학교육
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• 제36권2호
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• pp.113-128
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• 2017

This study aims to investigate the research trend of elementary environmental education. Thus, author keywords were extracted from a total of 197 academic these related to elementary environmental education during two different periods when detailed goals were applied to the 2007 and 2009 revised curriculums respectively, and then this study analyzed the network of author keywords. The results of this study can be summarized as below. Firstly, as a result of analyzing the frequency of author keywords from academic theses related to elementary environmental education, this study discovered 369 author keywords from the period when detailed goals were applied to 2009 revised curriculum. Out of them, it was found that the keyword, 'climate change education', showed the highest frequency, followed by 'environmental literacy' and 'environmental perception', except such central keywords as 'environmental education' and 'elementary school student'. From the period when detailed goals were applied to the 2007 revised curriculum, a total of 394 author keywords were discovered, and the keyword, 'environmental literacy', showed the highest frequency, followed by 'environmental perception' and 'ESD (education for sustainable development)'. Secondly, as a result of analyzing the network of author keywords, this study found out that in the total number of network connections, average connection degree, density and clique, the period when detailed goals were applied to the 2007 revised curriculum was somewhat higher than the period when detailed goals were applied to the 2009 revised curriculum. As a result of analyzing the centrality of author keywords, this study found out that during both the periods, 'environmental perception' and 'environmental literacy' were high in degree centrality and betweenness centrality, except such central keywords as 'environmental education' and 'elementary school student'. As a result of analyzing the components of author keywords as sub-networks, this study discovered 9 components from the period when detailed goals were applied to the 2009 revised curriculum and 6 components from the period when detailed goals were applied to the 2007 revised curriculum. During both the periods, the largest component was composed of keywords high in degree centrality and betweenness centrality.

• 정보관리학회지
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• 제29권2호
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• pp.225-246
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• 2012

본 연구는 국내 주요 학술 DB의 검색서비스에서 제공되고 있는 저자키워드(비통제키워드)의 재분류를 통하여 디스크립터(통제키워드)를 자동 할당할 수 있는 가능성을 모색하였다. 먼저 기계학습에 기반한 주요 분류기들의 특성을 비교하는 실험을 수행하여 재분류를 위한 최적 분류기와 파라미터를 선정하였다. 다음으로, 국내 독서 분야 학술지 논문들에 부여된 저자키워드를 학습한 결과에 따라 해당 논문들을 재분류함으로써 키워드를 추가로 할당하는 실험을 수행하였다. 또한 이러한 재분류 결과에 따라 새롭게 추가된 문헌들에 대하여 통제키워드인 디스크립터와 마찬가지로 동일 주제의 논문들을 모아주는 어휘통제 효과가 있는지를 살펴보았다. 그 결과, 저자키워드의 재분류를 통하여 디스크립터를 자동 할당하는 효과를 얻을 수 있음을 확인하였다.

• Journal of Information Processing Systems
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• 제16권2호
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• pp.447-459
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• 2020

After reading a document, people construct a concept about the information they consumed and merge multiple words to set up keywords that represent the material. With that in mind, this study suggests a smarter and more efficient keyword extraction method wherein scholarly journals are used as the basis for the establishment of production rules based on a concept information of words appearing in a document in a way in which author-provided keywords are functional although they do not appear in the body of the document. This study presents a new way to determine the importance of each keyword, excluding non-relevant keywords. To identify the validity of extracted keywords, titles and abstracts of journals about natural language and auditory language were collected for analysis. The comparison of author-provided keywords with the keyword results of the developed system showed that the developed system was highly useful, with an accuracy rate as good as up to 96%.

• Journal of Information Science Theory and Practice
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• 제7권1호
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• pp.29-38
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• 2019

Information retrieval is the challenge of the Web 2.0 world. The experiment of knowledge organisation in the context of abundant information available from various sources proves a major hurdle in obtaining information retrieval with greater precision and recall. The fast-changing landscape of information organisation through social networking sites at a personal level creates a world of opportunities for data scientists and also library professionals to assimilate the social data with expert created data. Thus, folksonomies or social tags play a vital role in information organisation and retrieval. The comparison of these user-created tags with expert-created index terms, author keywords and title words, will throw light on the differentiation between these sets of data. Such comparative studies show revelation of a new set of terms to enhance subject access and reflect the extent of similarity between user-generated tags and other set of terms. The CiteULike tags extracted from 5,150 scholarly journal articles in marine science were compared with corresponding Aquatic Science and Fisheries Abstracts descriptors, author keywords, and title terms. The Jaccard similarity coefficient method was employed to compare the social tags with the above mentioned wordsets, and results proved the presence of user-generated keywords in Aquatic Science and Fisheries Abstracts descriptors, author keywords, and title words. While using information retrieval techniques like stemmer and lemmatization, the results were found to enhance keywords to subject access.

• Journal of Information Science Theory and Practice
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• 제2권2호
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• pp.16-32
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• 2014

As Topic Modeling has been applied in increasingly various domains, the difficulty in naming and characterizing topics also has been recognized more. This study, therefore, explores an approach of combining text mining with network analysis in a multi-step approach. The concept of synchronization was applied to re-assign the top author keywords in more than one topic category, in order to improve the visibility of the topic-author keyword network, and to increase the topical cohesion in each topic. The suggested approach was applied using 16,548 articles with 2,881 unique author keywords in construction and building engineering indexed by KSCI. As a result, it was revealed that the combined approach could improve both the visibility of the topic-author keyword map and topical cohesion in most of the detected topic categories. There should be more cases of applying the approach in various domains for generalization and advancement of the approach. Also, more sophisticated evaluation methods should also be necessary to develop the suggested approach.

• 한국문헌정보학회지
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• 제48권4호
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• pp.297-322
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• 2014

본 연구의 목적은 KCI의 인문학, 사회과학, 예술체육 분야 저자키워드를 대상으로 의미적, 형태적 분석을 통해 기존에 연구된 개념범주 텍사노미의 적합성을 확인하고 실용적인 개선 방안을 제시하는 것이다. 연구를 통해 '실체, 추상, 일반/공통, 개체'의 네 개 최상위수준의 개념범주를 보다 구체적이고 핵심 개념이 반영된 일곱 개의 범주 '개체, 활동/기능, 특성, 이론/방법, 형식/틀, 일반/공통, 인스턴스'로 변경하였다. 중위범주와 하위범주의 경우 신설, 세분화, 통합, 삭제, 이동 등의 방법으로 개념범주의 계층 구조를 단순화시키고 범주 간 용어분포의 불균형을 개선하였다. 구조적학술용어사전(STNet)을 테스트베드로 삼아 수정된 개념범주 텍사노미를 적용한 결과 용어의 분포가 균형적으로 이루어지고, 용어의 속성 표현이 상세화되는 효과를 보이는 것으로 나타났다.

• 한국전자통신학회논문지
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• 제13권1호
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• pp.141-146
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• 2018

저자가 작성하는 논문의 저자 키워드는 논문 내용의 특징을 나타내는 가장 중요한 요소이며, 이를 실시간으로 분석하여 사용자에게 제공하게 함으로써, 연구동향을 파악하는 것이 가능하다. 서지로 작성된 논문의 비정형 데이터를 데이터베이스로 구축 하고, 이를 활용하여 실시간 탐색이 가능하도록 색인데이터 구조를 만든다. 특정 키워드가 포함된 논문을 색인데이터 구조에서 탐색하고, 저자키워드를 대상으로 추출, 클러스터링 하여 가중치에 따라 크기별로 나타낼 수 있는 워드클라우드로 사용자에게 제공하여, 연구동향을 가시화 하는 방법을 설계하였다. 또한, 구현된 시스템에서 "바이러스"와 "홍채인식" 키워드를 통하여 연구동향 분석 결과를 제시하였다.

• 대한통합의학회지
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• 제12권2호
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• pp.197-210
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• 2024

Purpose : This study aimed to analyze research trends in the field of integrative medicine through a bibliometric analysis of articles published in Integrative Medicine Research (IMR) journal from 2017 to 2022. Methods : Articles published in IMR journal between 2017 and 2022 were searched using the Web of Science database on August 22, 2023. The analysis was performed using the Bibliometrix and Biblioshiny tools in R (version 4.3.1) and VOSviewer (version 1.6.19). Results : The key findings were as follows: average citations per article (9.41), total authors (1,142), single-authored articles (12), average articles per author (0.27), average co-authors per article (5.27), and rate of international co-authorships (15.69 %). The most-cited article was on the cryopreservation of cells or tissues and their clinical applications. The top keyword analysis by author keywords showed that "acupuncture" was the most frequently used keyword (33 times). Co-occurrence network analysis showed 85 high-frequency keywords that appeared five or more times, and the top five keywords by total link strength were "acupuncture," "herbal medicine," "prevalence," "alternative medicine," and "complementary." The study found that, contrary to the trend in complementary and alternative medicine research in Korea, the IMR journal actively conducts intervention studies to provide clinical evidence. Conclusion : In the IMR journal, "acupuncture" was the most frequent of author keywords. The analysis of keyword trend topics over time showed that the keyword "systematic review" continued to appear from 2020 to 2022, and the keyword "clinical practice guideline" appeared for the first time in 2021. In particular, the co-occurrence network analysis highlighted keywords related to intervention research, in contrast to domestic research trends. While this study analyzed only one journal, future studies expanding the category of integrative medicine and increasing the number of journals analyzed may provide further insights.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2003년도 추계학술대회 및 정기총회
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• pp.107-110
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• 2003

The aim of this study is to map the intellectual structure of the field of Organic Light Emitting Diode(OLED). Co-word analysis was employed to reveal patterns and trends in the OLED field by measuring the association strengths of terms representative of relevant publications or other texts produced in OLED field. Data were collected from INSPEC. Important keywords were extracted from author keywords. These author keywords were further standardized. In order to trace the dynamic changes of the OLED field, present the technology mapping. The results show that the OLED field has some established research theme and it also changes rapidly to embrace new themes.

• 한국산학기술학회논문지
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• 제19권11호
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• pp.758-764
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• 2018

특허(patent), 학술 논문(scholarly paper)과 연구 보고서(research report)와 같은 디지털 문서(digital document)에는 주제(topic)를 요약하는 저자 키워드(author keyword)가 있다. 서로 다른 문서가 동일한 키워드를 공유하고 있다면 두 문서가 동일한 주제의 내용을 기술하고 있을 가능성이 매우 높다. 문서 군집화(document clustering)는 비슷한 주제를 가지는 문서들을 비지도 학습 방법(unsupervised learning)을 이용하여 같은 군집으로 그룹(group)화 하는 것이다. 문서 군집화는 다양한 분석에 이용되지만 대용량의 문서 데이터에 적용하기 위해서는 많은 계산량이 필요함으로 쉽지 않다. 이러한 경우, 문서의 내용을 이용하는 것보다 문서의 키워드를 이용하여 군집화하면 더욱 효율적으로 대용량의 데이터를 연결할 수 있다. 기존의 상향식 군집화 방법(bottom-up hierarchical clustering)은 대용량의 키워드 군집화(keyword clustering)를 수행하는데 있어서 많은 시간이 필요하다는 문제점이 있다. 본 논문에서는 정보검색(information retrieval)에서 널리 사용되는 역인덱스(inverted-index) 구조를 상향식 군집화에 적용한 효율적인 군집화 방법을 제안하고, 제안 방법을 대용량의 키워드 데이터에 적용하였으며, 그 결과를 분석하였다.