• Proceedings of the Korean Society for Information Management Conference
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• 2014.08a
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• pp.17-20
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• 2014

본 연구는 동시출현 단어분석 기법을 이용하여 최근 전세계적으로 많은 주목을 받고 있는 빅데이터(Big Data) 관련 연구 동향과 연구 영역을 분석하는 것을 목적으로 한다. 이를 위하여 인용색인데이터베이스인 Web of Science SCIE(Science Citation Index Expanded)에서 분석 대상 논문을 수집하였다. 논문 수집을 위한 검색식은 은 Title(논문 제목), Abstract(초록), Author Keywords(저자 키워드), Keywords $Plus^{(R)}$의 네 가지 필드를 동시에 검색하는 주제어(topic)가 "big data"를 포함하고 있는 논문 563편을 대상으로 동시출현단어 분석을 수행하였다.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.115-140
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• 2021

This study divided the keyword sets searched from LISTA database focusing on the overseas open access fields into two types (controlled keywords and uncontrolled keywords), and examined the results of performing an intellectual structure analysis based on profiling for the each keyword type. In addition, these results were compared with those of an intellectual structural analysis based on co-word analysis. Through this, I tried to investigate whether similar results were derived from profiling, another method of intellectual structure analysis, and to examine the differences between co-word analysis and profiling results. As a result, there was a similar difference to the co-word analysis in the results of intellectual structure analysis based on profiling for each of the two keyword types. Also, there were also noticeable differences between the results of intellectual structural analysis based on profiling and co-word analysis. Therefore, intellectual structure analysis using keywords should consider the characteristics of each keyword type according to the research purpose, and better results can be expected to be used based on profiling than co-word analysis to more clearly understand research trends in a specific field.

• 한국벤처창업학회:학술대회논문집
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• 2022.04a
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• pp.73-79
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• 2022

본 연구는 동시출현단어 분석과 토픽모델링을 통해 기업가정신의 연구주제와 연구 동향을 분석하여 기업가정신 연구에 대한 향후 연구방향을 수립하기 위한 정보를 제공하는 것이 목적이다. 이를 위해 Web of Science 데이터베이스에서 "entrepreneurship"을 기본검색어로 설정하고, 2002년부터 2021년까지 발표한 영어 논문으로 제한하여 기업가정신 논문의 데이터를 다운로드하여 데이터를 확보하였다. 본 연구에서는 VOSviewer 프로그램을 이용하여 동시출현단어 분석을 하였고, R 프로그램을 이용하여 토픽모델링 분석을 하였다. 동시출현단어 분석 결과, 기업가정신과 혁신 클러스터, 기업가정신 교육 클러스터, 사회적 기업가정신과 지속가능성 클러스터, 기업성과 클러스터, 그리고 지식 및 기술이전 클러스터 등 5개의 클러스터로 구분되었다. 토픽모델링 분석 결과, 창업환경 및 경제발전, 국제 기업가정신, 다양한 기업가정신, 벤처기업과 자본조달, 정부정책 및 지원, 사회적 기업가정신, 경영관련 이슈, 지역도시계획 및 개발, 기업가정신 교육, 기업가의 혁신과 성과, 기업가정신 연구, 기업가의 창업의도 등 12개의 토픽으로 분석되었다. 본 연구의 결과는 기업가정신 연구에 대한 전반적인 연구동향을 파악할 뿐만 아니라, 기업가정신과 관련된 어떠한 연구 주제들이 다루어져 왔는지에 대해 분석함으로써 기업가정신에 대한 연구의 이해도를 높이고 기업가정신 연구가 가져올 방향성을 제안하는데 활용할 수 있을 것으로 기대된다.

• Journal of the Korean Society for information Management
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• v.30 no.4
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• pp.195-213
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• 2013

This study aims at establishing the identity of teaching Korean as a Foreign Language (KFL) domain by using journal profiling and co-word analysis in comparison with the relevant and adjacent domains. Firstly, by extracting and comparing topic terms, we calculate the similarity of academic journals of the three domains, KFL, teaching Korean as a Native Language (KNL), and Korean Linguistics (KL). The result shows that the journals of KFL form a distinct cluster from the others. The profiling analysis and co-word analysis are then conducted to visualize the relationship among all the three domains in order to uncover the characteristics of KFL. The findings show that KFL is more similar to KNL than to KL. Finally, the comparison of knowledge structures of these three domains based on the co-word analysis demonstrates the uniqueness of KFL as an independent domain in relation with the other relevant domains.

• Journal of the Korean Society for information Management
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• v.28 no.3
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• pp.295-312
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• 2011

This study conducted time-series analysis on domestic studies related to entrepreneurship for more than last 50 years by integrating the co-word analysis method of intellectual structure analysis into the study of entrepreneurship. The co-word analysis method is a quantitative analysis method to analyze the overall trend of the study and further study topics by visualizing the information between study topics and arranging the topics on two-dimensional plane and the study result showed largely four phases and the direction of the study path. According to the analysis, the study is started at embryonic study phase(third quadrant), the study topic of independent study phase(second quadrant) is a phase to be a settled independent area as a study and the topics of the study include topics of the study reflecting the situation of the times. At growing study phase(first quadrant) study topics which are closely related to the study topic are arranged, and the topics, the center of the study, are positioned at the study topics of maturity phase(4th quadrant).

• Korean Journal of Environment and Ecology
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• v.33 no.1
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• pp.9-15
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• 2019

Artiodactyla, which is an even-toed mammal, widely inhabits worldwide. In recent years, wild Artiodactyla species have attracted public attention due to the rapid increase of crop damage and road-kill caused by wild Artiodactyla such as water deer and wild boar and the decrease of some species such as long-tailed goral and musk deer. In spite of such public attention, however, there have been few studies on Artiodactyla in Korea, and no studies have focused on the trend analysis of Artiodactyla, making it difficult to understand actual problems. Many recent studies on trend used text-mining and co-occurrence analysis to increase objectivity in the classification of research subjects by extracting keywords appearing in literature and quantifying relevance between words. In this study, we analyzed texts from research articles of three countries (Korea, China, and Japan) through text-mining and co-occurrence analysis and compared the research subjects in each country. We extracted 199 words from 665 articles related to Artiodactyla of three countries through text-mining. Three word-clusters were formed as a result of co-occurrence analysis on extracted words. We determined that cluster1 was related to "habitat condition and ecology", cluster2 was related to "disease" and cluster3 was related to "conservation genetics and molecular ecology". The results of comparing the rates of occurrence of each word clusters in each country showed that they were relatively even in China and Japan whereas Korea had a prevailing rate (69%) of cluster2 related to "disease". In the regression analysis on the number of words per year in each cluster, the number of words in both China and Japan increased evenly by year in each cluster while the rate of increase of cluster2 was five times more than the other clusters in Korea. The results indicate that Korean researches on Artiodactyla tended to focus on diseases more than those in China and Japan, and few researchers considered other subjects including habitat characteristics, behavior and molecular ecology. In order to control the damage caused by Artiodactyla and to establish a reasonable policy for the protection of endangered species, it is necessary to accumulate basic ecological data by conducting researches on wild Artiodactyla more.

• Journal of the Korean Society for information Management
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• v.31 no.1
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• pp.99-118
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• 2014

This paper carried out co-word analysis of noun and noun phrase using text-mining technique in order to grasp the research trends on domestic and international information science articles. It was conducted based on collected titles and articles of the papers published in the Journal of the Korean Society for Information Management (KOSIM) and Journal of American Society for Information Science and Technology (JASIST) from 1990 to 2013. By dividing whole period into five publication window, this paper was organized into the following processes: 1) analysis of high frequency co-word pair to examine the overall trends of both information science articles 2) analysis of each word appearing with high frequency keyword to grasp the detailed subject 3) focused network analysis of trend after 2010 when distinctively new keyword appeared. The result of the analysis shows that KOSIM has considerable portion of studies conducted regarding topics such as library, information service, information user and information organization. Whereas, JASIST has focused on studies regarding information retrieval, information user, web information, and bibliometrics.

• Journal of the Korean Society for information Management
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• v.30 no.2
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• pp.207-225
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• 2013

Due to the development of science and technology, the convergence of various disciplines has been fostered. Accordingly, interdisciplinary studies have increasingly been expanded by integrating knowledge and methodology from different disciplines. The primary focus of biblimetric methods is on investigating the intellectual structure a field, and analysis of the characterization of interdisciplinary studies is overlooked. In this study, we aim to identify the intellectual structure of the field of medical informatics through author co-citation analysis and co-word analysis by the representative journal "IEEE ENG MED BIOL." In addition, we examine authors and MeSH Terms of top three representative journals for further analysis of the field. We examine the intellectual structure of the medical informatics field by author and word clusters to identify the network structure of medical informatics disciplines.

• 한국IT서비스학회:학술대회논문집
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• 2005.05a
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• pp.222-230
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• 2005

컨버전스(Convergence)란 단어는 집합, 집중, 수렴, 한 곳으로 모여짐 등의 뜻을 지닌 일반적인 용어로써 매우 발전해가고 있는 IT 분야에서 다양한 수요자의 욕구와 기술의 진화에 따라 최근에 매우 빈번하게 등장하고 있는 용어이자, 중요한 화두 중에 하나가 되고 있다. 이에 단어가 지니고 있는 일반적 의미를 다각적으로 분석함과 동시에 그 의미가 정보통신분야의 기술적 측면에서 또한 활용적인 측면에서 어떤 암시와 효과를 나타내고 있고, 나아가 IT 분야의 발전을 향한 목표 지향적인 측면에서의 역할이 가능한지와 또 다른 발전과 진화에 따라 어느 정도의 생명력과 경쟁력은 지닐 수 있는지를 살펴보고자 한다. 20세기 후반에 등장한 새로운 산업의 빅뱅이 되고 있는 IT 분야가 전세계로 확산, 발전되어감에 따라 수많은 일반적인 단어와 용어 들이 정보통신분야에서 도입, 활용하였고 이러한 용어들은 단어 자체의 의미 보다는 정보통신분야 발전의 현재와 미래를 규정해왔고, 나아가 정보통신 발전에 따른 혜택을 받는 전세계와 국내의 이용자들에게 많은 변화를 제공함과 동시에 연관분야의 산업에도 긍정적이던 부정적이던지 상호간 막대한 영향을 미쳐왔다고 분석된다. 이에 본 논문 자료는 IT 전문 용어가 아닌 일반적인 용어 중에서 IT 분야의 어떤 형태로든 영향을 미칠 용어 중에서 컨버전스란 단어를 통해 IT 분야의 현주소를 사례를 중심으로 분석, 점검하고 향후 IT 분야에서 컨버전스가 적용될 미래의 발전 모습을 전망하고자 하는데 있다.

• Journal of the Korean Society for information Management
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• v.24 no.4
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• pp.285-303
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• 2007

This study aims to explore a new technique making complementary linkage between controlled vocabularies and uncontrolled vocabularies for analyzing a research domain. Co-word analysis can be largely divided into two based on the types of vocabulary used: controlled and uncontrolled. In the case of using controlled vocabulary, data sparseness and indexer effect are inherent drawbacks. On the other case, word selection by the author's perspective and word ambiguity. To complement each other, we suggest a descriptor profiling that represents descriptors(controlled vocabulary) as the co-occurrence with words from the text(uncontrolled vocabulary). Applying the profiling to the domain of information science implies that this method can complement each other by reducing the inherent shortcoming of the controlled and uncontrolled vocabulary.