• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.1
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• pp.207-228
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• 2013

Due to the advance of scholarly communication, the field of open access has been studied over the last decade. The purpose of this study is to analyze and demonstrate the field of open access via co-word analysis. The data set was collected from Web of Science citation database during the period from January 1998 to July 2012 using the Topic category. A total of 479 journal articles were retrieved and 8,643 noun keywords were extracted from the titles and abstracts. In order to achieve the purpose of this study, network analysis, clustering analysis and multidimensional scaling mapping were used to examine the domain and the sub-domains of open access field. 18 clusters in the network analysis are recognized and 4 clusters are shown in the map of multidimensional scaling. In addition, the centrality analysis in the weighted networks was used to explore the significant keywords in this field. The results of this study are expected to demonstrate and guide the intellectual structure and new approaches of open access field.

• The Journal of Korean Medicine
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• v.44 no.1
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• pp.38-55
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• 2023

Objectives: The purpose of this study was to provide direction for future research in the field of Korean medicine by analyzing microbiome based technologies emerging as a new diagnostic and treatment paradigm. Methods: To achieve the purpose of the study intellectual property data was used. After establishing citation network from registered microbiome-related US patents, citation network was analyzed by knowledge persistence-based main path approach to understanding technological trajectories. Furthermore, community detection algorithms were used to quantitatively identifying specific technological domain in a particular time period. Results: Results shows that early technologies in livestock industry contribute most to the recent patents. Knowledge in the patents flow through the path of food and beverage technological domain, and finally are inherited to the recent development of diagnosis, treatment and prevention technic. Conclusions: This study indicate that developing diagnostic tools which can link the composition of microbiome to specific diseases should be given high priority. Researches should lead to novel therapeutic strategies. Specifically, improving reliability of pattern identification and finding effective therapeutic compositions based on principles of Korean medicine is necessary.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.4
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• pp.311-331
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• 2023

This study attempted to explore the characteristics of knowledge communication and investigate important research topics and key authors by analyzing major academic papers in the field of LIS in Korea for five years from 2018 to 2022. The research method collected and analyzed papers published for five years in four key journals in the field of domestic Library and Information Science from the Korean Citation Index (KCI) database. The paper was selected to extract the author data of the paper and the data of the reference, and network visualization was performed by conducting literature co-citation analysis and author co-citation analysis using Netminer. As a result of the analysis, it was possible to derive a pair of co-citations between authors, and it was confirmed that it is important to include multiple authors in the intellectual structure analysis in the academic field through co-citation frequency analysis among researchers. The literature confirmed the correlation between the topics of the paper, and it was found that research related to Library and Information Science was centered on the topics of library, digital, user, service, and data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.473-476
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• 2003

Nowaday, Internet is doing the role of a large distributed information service tenter and various information and database servers managing it are in distributed network environment. However, the we have several difficulties in deciding the server to disposal input data depending on data properties. In this paper, we designed server mining mechanism and Intellectual data mining system architecture for the best efficiently dealing with input data pattern by using neural network among the various data in distributed environment. As a result, the new input data pattern could be operated after deciding the destination server according to dynamic binding method implemented by neural network. This mechanism can be applied Datawarehous, telecommunication and load pattern analysis, population census analysis and medical data analysis.

• The Journal of Information Systems
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• v.24 no.4
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• pp.43-60
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• 2015

Purpose This study intended to introduce new approaches to identify the intellectual structure of supply chain management(SCM) researches, which combines author co-citation analysis(ACA) and social network analysis(SNA). Design/methodology/approach We searched RISS(www.riss.kr) and NDSL(www.ndsl.or.kr) database and collected 292 academic papers on supply chain management between 2001 and 2011. Among 9,637 references of these papers, we analyzed 1,848 references that were published by domestic authors. We produced a correlation matrix of 32 author co-citation matrix and conducted multi-variate statistical analysis such as factor analysis. We also performed social network analysis to identify the main researchers in SCM. Findings We found four main sub-areas of supply chain management research: SCM adoption factors, logistics, SCM performance, and SCM structure. We could present the authors who played important roles within the network by using SNA indicators. The finding of this research also suggests more collaborations among domestic researchers are required to overcome the low co-citation rates among domestic authors.

• Journal of Korean Academy of Nursing
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• v.46 no.1
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• pp.50-58
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• 2016

Purpose: The purpose of this study was to identify the knowledge structure of cancer survivors. Methods: For data, 1099 articles were collected, with 365 keywords as a Noun phrase extracted from the articles and standardized for analyzing. Co-occurrence matrix were generated via a cosine similarity measure, and then the network analysis and visualization using PFNet and NodeXL were applied to visualize intellectual interchanges among keywords. Results: According to the result of the content analysis and the cluster analysis of author keywords from cancer survivors articles, keywords such as 'quality of life', 'breast neoplasms', 'cancer survivors', 'neoplasms', 'exercise' had a high degree centrality. The 9 most important research topics concerning cancer survivors were 'cancer-related symptoms and nursing', 'cancer treatment-related issues', 'late effects', 'psychosocial issues', 'healthy living managements', 'social supports', 'palliative cares', 'research methodology', and 'research participants'. Conclusion: Through this study, the knowledge structure of cancer survivors was identified. The 9 topics identified in this study can provide useful research direction for the development of nursing in cancer survivor research areas. The Network analysis used in this study will be useful for identifying the knowledge structure and identifying general views and current cancer survivor research trends.

• Korean Journal of Occupational Health Nursing
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• v.24 no.2
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• pp.76-85
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• 2015

Purpose: The purpose of this study was to identify knowledge structure of the Korean Journal of Occupational Health Nursing from 1991 to 2014. Methods: 400 articles between 1991 and 2014 were collected. 1,369 keywords as noun phrases were extracted from articles and standardized for analysis. Co-occurrence matrix was generated via a cosine similarity measure, then the network was analyzed and visualized using PFNet. Also NodeXL was applied to visualize intellectual interchanges among keywords. Results: According to the results of the content analysis and the cluster analysis of author keywords from the Korean Journal of Occupational Health Nursing articles, 7 most important research topics of the journal were 'Workers & Work-related Health Problem', 'Recognition & Preventive Health Behaviors', 'Health Promotion & Quality of Life', 'Occupational Health Nursing & Management', 'Clinical Nursing Environment', 'Caregivers and Social Support', and 'Job Satisfaction, Stress & Performance'. Newly emerging topics for 4-year period units were observed as research trends. Conclusion: Through this study, the knowledge structure of the Korean Journal of Occupational Health Nursing was identified. The network analysis of this study will be useful for identifying the knowledge structure as well as finding general view and current research trends. Furthermore, The results of this study could be utilized to seek the research direction in the Korean Journal of Occupational Health Nursing.

• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.17-24
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• 2009

This paper proposes a new e-learning model which introduces a participant method based on concepts of open source as well as UCC of web2.0 and achieves learner-centered learning. It is possible for learner to participate actively in creation of micro-contents and reorganize contents using various micro-content with one's learning strategies in consideration of one's own intellectual power, learning objectives and propensity to learn. The learner can achieve the learner-oriented learning through this procedure and select micro-contents in order to reorganize the personalized learning contents to take advantage of social network among learners. The higher effectiveness of learning would be expected by forming connectedness among learners using social network.

• Journal of Fashion Business
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• v.23 no.3
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• pp.51-66
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• 2019

The aim of this study is to identify research trends of "Journal of Fashion Business" by analyzing the keyword network of the paper published between 2006 and 2017. The papers selected for analysis in the study were 287 fashion design articles and 281 fashion marketing articles published between February 2006 and December 2017 and titles, volumes, publishing years, authors, keywords, and abstracts of each paper were collected for data analysis. The research was carried out through selection, collection of article data, keyword extraction and coding, keywords refinement, formation of network matrix, and analysis and visualization process. First, based on the title of the paper used in the analysis, the fashion design/aesthetics, marketing/social psychology, clothing materials, clothing composition, and other fields were classified. Research analysis used the Netminer 4 (Ver.4.3.2) program. Results indicated showed that the intellectual structure of the "Fashion Business" research paper showed key word changes over time, and the degree centrality and between centrality of the keywords.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.1
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• pp.393-413
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• 2021

Digital humanities, which creates new and innovative knowledge through the combination of digital information technology and humanities research problems, can be seen as a representative multidisciplinary field of study. To investigate the intellectual structure of the digital humanities field, a network analysis of authors and keywords co-word was performed on a total of 441 papers in the last two years (2019, 2020) at the Digital Humanities Conference. As the results of the author and keyword analysis show, we can find out the active activities of Europe, North America, and Japanese and Chinese authors in East Asia. Through the co-author network, 11 dis-connected sub-networks are identified, which can be seen as a result of closed co-authoring activities. Through keyword analysis, 16 sub-subject areas are identified, which are machine learning, pedagogy, metadata, topic modeling, stylometry, cultural heritage, network, digital archive, natural language processing, digital library, twitter, drama, big data, neural network, virtual reality, and ethics. This results imply that a diver variety of digital information technologies are playing a major role in the digital humanities. In addition, keywords with high frequency can be classified into humanities-based keywords, digital information technology-based keywords, and convergence keywords. The dynamics of the growth and development of digital humanities can represented in these combinations of keywords.