• Title/Summary/Keyword: 키워드네트워크 분석

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Research Trend Analysis Using Bibliographic Information and Citations of Cloud Computing Articles: Application of Social Network Analysis (클라우드 컴퓨팅 관련 논문의 서지정보 및 인용정보를 활용한 연구 동향 분석: 사회 네트워크 분석의 활용)

  • Kim, Dongsung;Kim, Jongwoo
    • Journal of Intelligence and Information Systems
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    • v.20 no.1
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    • pp.195-211
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    • 2014
  • Cloud computing services provide IT resources as services on demand. This is considered a key concept, which will lead a shift from an ownership-based paradigm to a new pay-for-use paradigm, which can reduce the fixed cost for IT resources, and improve flexibility and scalability. As IT services, cloud services have evolved from early similar computing concepts such as network computing, utility computing, server-based computing, and grid computing. So research into cloud computing is highly related to and combined with various relevant computing research areas. To seek promising research issues and topics in cloud computing, it is necessary to understand the research trends in cloud computing more comprehensively. In this study, we collect bibliographic information and citation information for cloud computing related research papers published in major international journals from 1994 to 2012, and analyzes macroscopic trends and network changes to citation relationships among papers and the co-occurrence relationships of key words by utilizing social network analysis measures. Through the analysis, we can identify the relationships and connections among research topics in cloud computing related areas, and highlight new potential research topics. In addition, we visualize dynamic changes of research topics relating to cloud computing using a proposed cloud computing "research trend map." A research trend map visualizes positions of research topics in two-dimensional space. Frequencies of key words (X-axis) and the rates of increase in the degree centrality of key words (Y-axis) are used as the two dimensions of the research trend map. Based on the values of the two dimensions, the two dimensional space of a research map is divided into four areas: maturation, growth, promising, and decline. An area with high keyword frequency, but low rates of increase of degree centrality is defined as a mature technology area; the area where both keyword frequency and the increase rate of degree centrality are high is defined as a growth technology area; the area where the keyword frequency is low, but the rate of increase in the degree centrality is high is defined as a promising technology area; and the area where both keyword frequency and the rate of degree centrality are low is defined as a declining technology area. Based on this method, cloud computing research trend maps make it possible to easily grasp the main research trends in cloud computing, and to explain the evolution of research topics. According to the results of an analysis of citation relationships, research papers on security, distributed processing, and optical networking for cloud computing are on the top based on the page-rank measure. From the analysis of key words in research papers, cloud computing and grid computing showed high centrality in 2009, and key words dealing with main elemental technologies such as data outsourcing, error detection methods, and infrastructure construction showed high centrality in 2010~2011. In 2012, security, virtualization, and resource management showed high centrality. Moreover, it was found that the interest in the technical issues of cloud computing increases gradually. From annual cloud computing research trend maps, it was verified that security is located in the promising area, virtualization has moved from the promising area to the growth area, and grid computing and distributed system has moved to the declining area. The study results indicate that distributed systems and grid computing received a lot of attention as similar computing paradigms in the early stage of cloud computing research. The early stage of cloud computing was a period focused on understanding and investigating cloud computing as an emergent technology, linking to relevant established computing concepts. After the early stage, security and virtualization technologies became main issues in cloud computing, which is reflected in the movement of security and virtualization technologies from the promising area to the growth area in the cloud computing research trend maps. Moreover, this study revealed that current research in cloud computing has rapidly transferred from a focus on technical issues to for a focus on application issues, such as SLAs (Service Level Agreements).

Strategic Behavioral Characteristics of Co-opetition in the Display Industry (디스플레이 산업에서의 협력-경쟁(co-opetition) 전략적 행동 특성)

  • Jung, Hyo-jung;Cho, Yong-rae
    • Journal of Korea Technology Innovation Society
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    • v.20 no.3
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    • pp.576-606
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    • 2017
  • It is more salient in the high-tech industry to cooperate even among competitors in order to promptly respond to the changes in product architecture. In this sense, 'co-opetition,' which is the combination word between 'cooperation' and 'competition,' is the new business term in the strategic management and represents the two concepts "simultaneously co-exist." From this view, this study set up the research purposes as follows: 1) investigating the corporate managerial and technological behavioral characteristics in the co-opetition of the global display industry. 2) verifying the emerging factors during the co-opetition behavior hereafter. 3) suggesting the strategic direction focusing on the co-opetition behavioral characteristics. To this end, this study used co-word network analysis to understand the structure in context level of the co-opetition. In order to understand topics on each network, we clustered the keywords by community detection algorithm based on modularity and labeled the cluster name. The results show that there were increasing patterns of competition rather than cooperation. Especially, the litigations for mutual control against Korean firms much more severely occurred and increased as time passed by. Investigating these network structure in technological evolution perspective, there were already active cooperation and competition among firms in the early 2000s surrounding the issues of OLED-related technology developments. From the middle of the 2000s, firm behaviors have focused on the acceleration of the existing technologies and the development of futuristic display. In other words, there has been competition to take leadership of the innovation in the level of final products such as the TV and smartphone by applying the display panel products. This study will provide not only better understanding on the context of the display industry, but also the analytical framework for the direction of the predictable innovation through analyzing the managerial and technological factors. Also, the methods can support CTOs and practitioners in the technology planning who should consider those factors in the process of decision making related to the strategic technology management and product development.

Analysis of Research Trends in Relation to the Yellow Sea using Text Mining (텍스트 마이닝을 활용한 황해 관련 연구동향 분석연구)

  • Kyu Won Hwang;Kim Jinkyung;Kang Seung-Koo;Kang Gil Mo
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.7
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    • pp.724-739
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    • 2023
  • Located in the sea area between South Korea, North Korea, and China, the Yellow Sea plays an important role from a geopolitical perspective, and recently, as the use of marine space in the Yellow Sea is expanding, its social and economic values have been increasing further. In addition, owing to rapid climate changes, the need for joint response and cooperation between Korea and China is increasing in various fields, including changes in the marine environment and marine ecosystem and generation and movement of air pollutants. Accordingly, in this study, core topics were derived from research papers with the Yellow Sea as a keyword, and research trends to date were explored through author network analysis. As a specific research method, research papers related to the Yellow Sea published between 1984 and 2021 were extracted from the Web of Science database and were classified into four periods to derive core topics using topic modeling, a type of text mining. Furthermore, the influences of major research communities, researchers, and research institutes in the appropriate fields were identified through analyzing the author network, and their implications were presented. The analysis results indicated that the core topics of research papers on the Yellow Sea had changed over time, and differences existed in the influence (centrality) of key researchers. Finally, based on the results of this study, this study aims to identify research trends related to the Yellow Sea, major researchers, and research institutes and contribute to research cooperation between Korea and China regarding the Yellow Sea in the future.

Analyzing the Trends of Culture Technology using National Research Projects (문화기술(CT) 연구 동향 분석: 국가연구과제를 중심으로)

  • Lee, Beom-Hun;Jeon, Woojin;Geum, Youngjung
    • The Journal of the Korea Contents Association
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    • v.21 no.11
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    • pp.64-76
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    • 2021
  • Culture technology (CT) becomes important in the recent environment where digital technology drives content-based innovations. However, technological trends of CT have not been systematically discussed. Especially, the trends of CT should be analyzed from the national perspective, because CT has grown with the help of government-driven innovation. Therefore, this paper aims to analyze CT trends focusing on national research projects. We collected data on CT from the national science and technology information service (NTIS) database, analyzed the keyword co-occurrence network, and identified the patterns of technological innovation using a clustering analysis. As a result, we found that CT has contributed to the digital content and cultural media, and has been actively developed with the help of machine learning technique. Especially, due to the rise of Covid-19, the non-face-to-face online content is rapidly increasing. This study provides important clues for understanding, analyzing CT trends.

Visualizing Unstructured Data using a Big Data Analytical Tool R Language (빅데이터 분석 도구 R 언어를 이용한 비정형 데이터 시각화)

  • Nam, Soo-Tai;Chen, Jinhui;Shin, Seong-Yoon;Jin, Chan-Yong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.151-154
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    • 2021
  • Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study was analyzed for 21 papers in the March 2021 among the journals of the Korea Institute of Information and Communication Engineering. In the final analysis results, the most frequently mentioned keyword was "Data", which ranked first 305 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

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Visualizing Article Material using a Big Data Analytical Tool R Language (빅데이터 분석 도구 R 언어를 이용한 논문 데이터 시각화)

  • Nam, Soo-Tai;Shin, Seong-Yoon;Jin, Chan-Yong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.326-327
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    • 2021
  • Newly, big data utilization has been widely interested in a wide variety of industrial fields. Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study were analyzed for 29 papers in a specific journal. In the final analysis results, the most frequently mentioned keyword was "Research", which ranked first 743 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

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Tendency Analyze the Core Policies of Local Government Directors (지방자치단체장의 주요정책 경향분석(I):민선 5기 선거공약을 중심으로)

  • Choi, Ho-Taek;Ryu, Sang-Il;Jung, Seok-Hwan;Lee, Min-Kyu
    • The Journal of the Korea Contents Association
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    • v.12 no.12
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    • pp.661-671
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    • 2012
  • The purpose of this study was to analyze the core policies of local government directors by performing centrality analysis on their core policies using network text analysis method. From the research results, it was verified to some extent that major policies of local government directors were changing during the path to arrive at 5th civil election. However, according to policy type by Peterson (development policy, allocation policy and redistribution policy) it was found that they still focused on development policies. However, it is encouraging that the government directors elected in the 5th election started to pay attention to 'Culture' which is one of allocation policies.

A Study on the Analysis of Influx Factors in Urban Parks Using Data Mining - Focus on Yangjae Citizens' Forest Park - (데이터 마이닝을 활용한 도시공원 유입 요인 분석 연구 - 양재시민의 숲 공원을 대상으로 -)

  • Park Sang Hun
    • Journal of the Korean Regional Science Association
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    • v.39 no.3
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    • pp.35-48
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    • 2023
  • This study analyzed the inflow factors of Yangjae Citizen's Forest Park using social big data generated online. To this end, the applicability of the emotional information analysis method is to be confirmed as a method of analyzing the perception of the city park and confirming the difference in the characteristics and use of the park. The analysis is based on big data, and as the core of the study is keyword network analysis, the methodology of the 'emotional information analysis method' patented by the author was applied. As a result of the analysis, among the influx factors of Yangjae Citizens' Forest recognized by citizens, the most positive emotional factor was derived as a factor related to 'park contents', and the negative emotional factor was derived as a factor related to 'park management'. These research results suggest that more in-depth program development and operation are needed to discover 'park contents' when implementing urban park revitalization support projects in the future

Crepe Search System Design using Web Crawling (웹 크롤링 이용한 크레페 검색 시스템 설계)

  • Kim, Hyo-Jong;Han, Kun-Hee;Shin, Seung-Soo
    • Journal of Digital Convergence
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    • v.15 no.11
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    • pp.261-269
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    • 2017
  • The purpose of this paper is to provide a search system using a method of accessing the web in real time without using a database server in order to guarantee the up-to-date information in a single network, rather than using a plurality of bots connected by a wide area network Design. The method of the research is to design and analyze the system which can search the person and keyword quickly and accurately in crepe system. In the crepe server, when the user registers information, the body tag matching conversion process stores all the information as it is, since various styles are applied to each user, such as a font, a font size, and a color. The crepe server does not cause a problem of body tag matching. However, when executing the crepe retrieval system, the style and characteristics of users can not be formalized. This problem can be solved by using the html_img_parser function and the Go language html parser package. By applying queues and multiple threads to a general-purpose web crawler, rather than a web crawler design that targets a specific site, it is possible to utilize a multiplier that quickly and efficiently searches and collects various web sites in various applications.

Information Security Job Skills Requirements: Text-mining to Compare Job Posting and NCS (정보보호 직무 수행을 위해 필요한 지식 및 기술: 텍스트 마이닝을 이용한 구인광고와 NCS의 비교)

  • Hyo-Jung Jun;Byeong-Jo Park;Tae-Sung Kim
    • Information Systems Review
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    • v.25 no.3
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    • pp.179-197
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    • 2023
  • As a sufficient workforce supports the industry's growth, workforce training has also been carried out as part of the industry promotion policy. However, the market still has a shortage of skilled mid-level workers. The information security disclosure requires organizations to secure personnel responsible for information security work. Still, the division between information technology work and job areas is unclear, and the pay is not high for responsibility. This paper compares job keywords in advertisements for the information security workforce for 2014, 2019, and 2022. There is no difference in the keywords describing the job duties of information security personnel in the three years, such as implementation, operation, technical support, network, and security solution. To identify the actual needs of companies, we also analyzed and compared the contents of job advertisements posted on online recruitment sites with information security sector knowledge and skills defined by the National Competence Standards used for comprehensive vocational training. It was found that technical skills such as technology development, network, and operating system are preferred in the actual workplace. In contrast, managerial skills such as the legal system and certification systems are prioritized in vocational training.