• 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.

• Proceedings of the Korean Society for Information Management Conference
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• 2000.08a
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• pp.63-66
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• 2000

본 연구는 인터넷상에서 제공되는 지적콘텐츠에 대한 영속적이고 고유한 식별 체계인 DOI 상용 서비스의 일환으로 DOI 구문을 구성하고 있는 Prefix와 Suffix 식별코드를 개발하였다. 이를 위해서 현재 인터넷상에서 지적콘텐츠를 유통시키고 있는 기관들을 조사 분류하여 콘텐츠 보유기관 식별코드를 개발하였다. 또한 지적콘텐츠의 속성 및 유형 분석을 토대로 Suffix 코드의 구조 및 식별코드를 개발하였으며 관련 콘텐츠간의 연계를 위한 저작권 식별기호를 고려하였다.

• The Journal of the Convergence on Culture Technology
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• v.1 no.4
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• pp.27-43
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• 2015

The objective of this study is to find out the construct of intellectual capital in a fashion company. To this end, the mixed research methods that combined qualitative and quantitative approaches were conducted. Qualitative research was first conducted by in-depth interviews with 16 experts working in the fashion industry, and a questionnaire was then given to 121 fashion companies in order to fulfill the quantitative research portion of this study. The findings of this study are as follows: First, the conceptual structure of intellectual capital in a fashion company was revealed. A fashion company's intellectual capital is composed of 'human capital', 'structural capital', and 'relational capital'. Human capital has three components: a chief executive officer (CEO), members, and a human resource management capability. Structural capital has four components: organizational culture, information management capability, merchandising capability, and product innovation capability. Relational capital has three components: customer equity, marketing capability, and relationship management capability. Second, the conceptual structure of intellectual capital was confirmed via quantitative research analysis. All of the components of intellectual capital have internal consistency, convergent validity, construct validity, and discriminant validity.

• Journal of Korean Library and Information Science Society
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• v.50 no.1
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• pp.333-356
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• 2019

Open access has emerged as an alternative to overcome the crisis brought by scholarly communication on commercial publishers. The purpose of this study is to suggest the intellectual structure that reflects the newest research trend in the field of open access, to identify how the subject area is structured by using co-word analysis, and compare and analyze with the existing study. In order to do this, the total number of dataset was 761 papers collected from Web of Science during the period from January 2012 to November 2018 using information science and 2,321 keywords as a noun phase are extracted from titles and abstracts. To analyze the intellectual structure of open access, 13 topic clusters are extracted by network analysis and the keywords with higher centrallity are drawn by visualizing the intellectual relationship. In addition, after clustering analysis, the relationship was analyzed by plotting the result on the multidimensional scaling map. As a result, it is expected that our research helps the research direction of open access for the future.

• The Journal of Engineering Geology
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• v.31 no.3
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• pp.307-319
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• 2021

Although it is currently conducting slope management and research using digital technologies such as drones, big data, and artificial intelligence, it is still somewhat insufficient and is still vulnerable to slope failure. For this reason, it is inevitable to present the development direction for research on prediction and analysis of slope failure using the digital technologies to effectively deal with slope failure, which requires a preemptive understanding of prediction and analysis of slope failure. In this paper, we collected literature data based on the Web of Science for five years from January 1, 2016 to December 31, 2020 and analyzed by co-word analysis to identify the domain structure of research on prediction and analysis of slope failure. Detailed subject areas were identified through network analysis, and the domain relationships between keywords were visualized to derive global and regionally oriented keywords through relationship, centrality analysis. In addition, the clusters formed by performing cluster analysis were displayed on the multidimensional scailing map, and the domain structure according to the correlation between each keyword was presented. The results of this study reveal the domain structure of research on prediction and analysis of slope failure, and are expected to be usefully used to find future research directions.

• KOREAN POULTRY JOURNAL
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• v.31 no.1 s.351
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• pp.38-42
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• 1999

• Journal of the Korean Society for information Management
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• v.34 no.4
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• pp.101-126
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• 2017

Data Science is emerging as a closely related field of study to Library and Information Science (LIS), and as an interdisciplinary subject combining LIS, statistics and computer science in an attempt to understand the value of data by applying what LIS has been doing for collecting, storing, organizing, analyzing, and utilizing information. To investigate which subject fields other than LIS, statistics, and computer science are related to Data Science, this study retrieved 667 materials from Web of Science Core Collection, extracted terms representing Web of Science Categories, examined subject fields that are studying Data Science using descriptive analysis, analyzed the intellectual structure of the field by co-word analysis and network analysis, and visualized the results as a Pathfinder network with clustering created with the PNNC clustering algorithm. The result of this study might help to understand the intellectual structure of the Data Science field, and may be helpful to give an idea for developing relatively new curriculum.

• Journal of Information Management
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• v.43 no.2
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• pp.43-66
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• 2012

The purpose of this study is to see the intellectual structure in the field of veterinary sciences in Korea, using author profiling analysis(APA), a bibliometric approach. Three journals are selected on the basis of citation data, exchanging most citations with Korean Journal of Veterinary. And then, 50 authors who published most articles at selected journals during the given period of time were chosen. The analysis of similarity and dissimilarity among authors by comparing co-word appearance patterns from article title, abstracts, and keywords was made. Authors can be grouped 11 minor clusters under 4 major clusters, depending on their interests in the area of veterinary sciences in Korea. The subjects for each cluster at the veterinary sciences are decided by the matching the keyword, representing author's research interest. As a result, it is possible to figure out the current research trends and the researcher network in the field of veterinary sciences.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.127-140
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• 2022

With the recent development of the ICT (information and communication technology), the revolution of the industry has moved on from the third industry to the fourth. There is no doubt that the companies would not survive in the future without adopting these technologies. The purpose of this research is to analyze the intellectual structure of the internet of things(IoT) literature for the Industry 4.0 to suggest a better insight for the field. The data for this research is extracted from the Web of Science database. Total of 1,631 documents and 72,754 references are used for the research with the analysis program CiteSpace. Author co-citation analysis is used to analyze the intellectual structure and performed clustering, timeline and burst detection analysis. We identified 12 sub-areas of IoT for the Industry 4.0 which are 'Supply Chain', 'Digital Twin', 'Smart Manufacturing System' and etc. Through the timeline analysis we can find out which clusters will increase or decrease its reputation. As concluding remarks, limitations and further research suggestions are discussed.

• Journal of the Korean Society for information Management
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• v.9 no.1
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• pp.55-82
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• 1992

It can be assumed that exciting improvements of technology concerning the ways in which information is stored and processed have significantly affected information science and may lead to a dramatic change of research in the field. Author co-citation analysis was used to investigate changes in research patterns of information retrieval over two time periods, 1980-1982, and 1988-1990. Nonmetric multidimensional scaling and clustering techiqes were used to create two dimensional maps displaying the changing research patterns among 22 authors as perceived by scholars citing their work over the two time periods. The co-cited author clusters and the placement of authors on the two maps both appear to correspond well with characterizations of the author's work obtained in texts and social relationships.