• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.203-210
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• 2020

In order to sustainably develop economy of regions and countries, it is necessary to pay attention to formation of new clusters from a long-term perspective. This study examined concepts and characteristics of clusters, and analyzed conditions related to emergence of clusters based on previous studies. Then, this study derived important factors and intended to propose a framework that is possible to help analyze clusters in the future. The development stages were divided into four stages of occurrence, growth, maturity, and decline. As for emergence conditions, entrepreneurship, institutional support, decision factors by development stages, and requirements for the future cluster success were presented. This study has academic significance in that it presents an integrated framework to analyze cluster emergence, and based on it, this study also presents directions of future studies and the regional and national policy implications. However, this study has many limitations in that it is difficult to generalize because it has not considered all variables in various dimensions and environments.

• 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.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.3
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• pp.245-256
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• 2022

The purpose of this study is to provide comprehensive insights on the current research trends in entrepreneurship based on topic modeling and keyword co-occurrence analysis. This study queried Web of Science database with 'entrepreneurship' and collected 14,953 research articles between 2002 and 2021. The study used R program for topic modeling and VOSviewer program for keyword co-occurrence analysis. The results of this study are as follows. First, as a result of keyword co-occurrence analysis, 5 clusters divided: entrepreneurship and innovation cluster, entrepreneurship education cluster, social entrepreneurship and sustainability cluster, enterprise performance cluster, and knowledge and technology transfer cluster. Second, as a result of the topic modeling analysis, 12 topics found: start-up environment and economic development, international entrepreneurship, venture capital, government policy and support, social entrepreneurship, management-related issues, regional city planning and development, entrepreneurship research, and entrepreneurial intention. Finally, the study identified two hot topics(venture capital and entrepreneurship intention) and a cold topic(international entrepreneurship). The results of this study are useful to understand current research trends in entrepreneurship research and provide insights into research of entrepreneurship.

• Proceedings of the KAIS Fall Conference
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• 2012.05a
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• pp.205-208
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• 2012

2차 세계대전 이후 현대음악은 기존의 12음 기법을 유지하면서 이전과는 다른 음소재(音素材)나 작법(作法)이 출현하게 되었다. 이중 온음 이내의 좁은 음정간격에서 다수의 음이 나는 톤 클러스터(Tone Cluster)는 현대음악에서 작곡기법으로 사용되고 있다. 이러한 클러스터 보이싱은 재즈음악과 대중음악에서도 종종 사용되고 있으며 본 연구를 통해 다양한 클러스터 보이싱을 만들어 보고 적용시켜 보았다.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.26 no.4
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• pp.245-262
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• 2015

As the topics of general education in universities become more diverse, it is not an easy task to identify the topics of general education courses. This study aims to identify and visualize the topics of A university's general education courses using informetric analysis methods. 214 syllabi were collected and titles, course introduction, goals, and weekly plans were analyzed. 278 topic words were extracted from the data set and grouped into 8 clusters. In the network analysis, topic clusters were divided into two areas, personal and social. Personal area has 14 sub-topic clusters and social area has 11 sub-topic clusters. In personal area, 'language', 'science', and 'personality' were major topic clusters. In social area, 'multi-culture' cluster was the core cluster with connected to four other clusters. The topic network generated in this study can be used for the university and the university library to enhance general education or to develop collections for general education.

• Journal of Korea Technology Innovation Society
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• v.21 no.4
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• pp.1207-1236
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• 2018

This paper explores the life cycle of innovation cluster, especially focussing on the Korean representative innovation cluster, Daedeok Innopolis. For this purpose, we review theoretically how an innovation cluster has been growing up. In particular, we discuss how a cluster has been formed and activated by governmental innovation policies from an evolutionary perspective. By doing so, the study identifies the typical features of an innovation cluster according to each dimensions of the cluster life cycle. The results of this study are as follows: First, in this study, Daedeok Innopolis has characteristics of latency, emergence, growth, and maturity from evolutionary perspective. Second, the governmental structure of the Daedeok Innopolis is a strong government-led and top-down structure, which has features of inclusiveness and flexibility such as umbrella policy. Third, the Daedeok Innopolis can be seen that adaptive or renewal development, as while, it can be applied fine adjustment the innovation cluster policy towards the recognition of innovation obstacle at each dimensions of the life cycle. Therefore, these discussions expose what kind of policy interventions should be addressed to form and develop the innovation cluster according to the cluster life cycle, as while, the development of adaptive policies during the risk and take-off period. Ultimately, the study provides that a different kind of policy instruments and tools should be implemented according to innovation cluster development and its distinctive characteristic per each dimensions of the cluster life cycle.

• Journal of Internet Computing and Services
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• v.18 no.2
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• pp.61-73
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• 2017

In this paper, we propose a Documents Cluster Labeling method using information content of words in clusters to understand what the clusters imply. To do so, we calculate the weight and frequency of the words. These two measures are used to determine the weight among the words in the cluster. As a nest step, we identify the candidate labels using the WordNet. At this time, the candidate labels are matched to least common hypernym of the words in the cluster. Finally, the representative labels are determined with respect to information content of the words and the weight of the words. To prove the superiority of our method, we perform the heuristic experiment using two kinds of measures, named the suitability of the candidate label ($Suitability_{cl}$) and the appropriacy of representative label ($Appropriacy_{rl}$). In applying the method proposed in this research, in case of suitability of the candidate label, it decreases slightly compared with existing methods, but the computational cost is about 20% of the conventional methods. And we confirmed that appropriacy of the representative label is better results than the existing methods. As a result, it is expected to help data analysts to interpret the document cluster easier.

• Journal of Information Management
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• v.35 no.3
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• pp.125-138
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• 2004

The purpose of this study is to propose a hierarchical user interfaces for browsing the knowledge structure of a single document. To generate the hierarchical knowledge structure, hierarchical term clustering and cluster representative term selection were performed with a single thesis in information science field, and the result was applied to design the interfaces which browse a single document hierarchically using multidimensional scaling. The interfaces can be applied to develop the user-friendly information retrieval system.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.127-136
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• 2024

This study explores the correlation between system anomalies and large-scale logs within the Spark cluster environment. While research on anomaly detection using logs is growing, there remains a limitation in adequately leveraging logs from various components of the cluster and considering the relationship between anomalies and the system. Therefore, this paper analyzes the distribution of normal and abnormal logs and explores the potential for anomaly detection based on the occurrence of log templates. By employing Hadoop and Spark, normal and abnormal log data are generated, and through t-SNE and K-means clustering, templates of abnormal logs in anomalous situations are identified to comprehend anomalies. Ultimately, unique log templates occurring only during abnormal situations are identified, thereby presenting the potential for anomaly detection.

• Journal of the Korean Society for Library and Information Science
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• v.38 no.1
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• pp.35-50
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• 2004

This study evaluated the applicability of the static hierarchic clustering model to clustering query results in OPAC. Two clustering methods(Between Average Linkage(BAL) and Complete Linkage(CL)) and two similarity coefficients(Dice and Jaccard) were tested on the query results retrieved from 16 title-based keyword searchings. The precision of optimal dusters was improved more than 100% compared with title-word searching. There was no difference between similarity coefficients but clustering methods in optimal cluster effectiveness. CL method is better in precision ratio but BAL is better in recall ratio at the optimal top-level and bottom-level clusters. However the differences are not significant except higher recall ratio of BAL at the top-level duster. Small number of clusters and long chain of hierarchy for optimal cluster resulted from BAL could not be desirable and efficient.