• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3029-3042
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• 2022

For over half a century, the United States (US) and its coalition military aircrafts have been using Ultra High Frequency (UHF) band analog modulation (AM) radios in ground-to-air communication and short-range air-to-air communications. Evolving from this, since 2007, the US military and the North Atlantic Treaty Organization (NATO) adopted HAVE QUICK to be used by almost all aircrafts, because it had been revealed that intercepting and jamming of former aircraft communication signals was possible, which placed a serious threat to defense systems. The second-generation Anti-jam Tactical UHF Radio for NATO (SATURN) was developed to replace HAVE QUICK systems by 2023. The NATO Standardization Agreement (STANAG) 4372 is a classified document that defines the SATURN technical and operational specifications. In preparation of this future upgrade to SATURN systems, in this paper, the SATURN technical and operational specifications are reviewed, and the network synchronization, frequency hopping, and communication setup parameters that are controlled by the Network (NET) Time, Time Of Day (TOD), Word Of Day (WOD), and Multiple Word of Day (MWOD) are described in addition to SATURN Edition 3 (ED3) and future Edition 4 (ED4) basic features. In addition, an anti-jamming performance analysis (in reference to partial band jamming and pulse jamming) and the time delay queueing model analysis are conducted based on a SATURN transmitter and receiver assumed model.

• 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.

• Journal of the Korean Society for information Management
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• v.30 no.1
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• pp.285-302
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• 2013

This study identified topic shifts and patterns over time by analyzing an enormous amount of Twitter data whose characteristics are high accessibility and briefness. First, we extracted keywords for a certain product and used them for representing the topic network allows for intuitive understanding of keywords associated with topics by nodes and edges by co-word analysis. We conducted temporal analysis of term co-occurrence as well as topic modeling to examine the results of network analysis. In addition, the results of comparing topic shifts on Twitter with the corresponding retrieval results from newspapers confirm that Twitter makes immediate responses to news media and spreads the negative issues out quickly. Our findings may suggest that companies utilize the proposed technique to identify public's negative opinions as quickly as possible and to apply for the timely decision making and effective responses to their customers.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.25 no.1
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• pp.295-318
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• 2014

The purpose of this study is to analyze the intellectual structure of reading studies by using Co-Word Analysis based on the mixed weight in which the level of academic journals and the position of keywords are calculated. To achieve it, 838 academic articles relating to reading studies from KCI during the period from 2003 to 2012 were retrieved and 56 keywords were extracted. The results of clustering analysis, MDS, network analysis are that the network based on the mixed weight has a better performance in above three methods and reading studies can be divided into 4 bigger divisions and 11 subdivisions. Finally, the result of document analysis shows reading studies changes its research tendency from theoretical studies to empirical studies.

• 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.

• Journal of Korean Library and Information Science Society
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• v.42 no.4
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• pp.353-374
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• 2011

Analyzing research paper published from 2005 to 2010, this study aims for analysing the research paradigm on multi-culture and understanding the structural characteristics of the multicultural knowledge via scientometric. Co-word network constructed by keywords in documents and their co-occurrence relationships is a kind of mapping knowledge structure. A total of 4,521 and 1,373 papers published between 2005 and 2010 were retrieved from the KRF Registered Journals and Proposed Journals. This paper employs k-core analysis method in the field of mapping knowledge structure to analyze keyword co-occurrence network of multicultural research in Korea. And Netminer 3 is employed to visualize the networks in this paper.

• 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 the Korean Society for information Management
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• v.31 no.4
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• pp.161-178
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• 2014

Recently, many information services allow users to collaborate to produce and use information. Sharing information is also important for users who have similar taste or interest. As various channels are available for users to share their experiences and knowledge, users' data have also been accumulated within the information services. This study collected movie lists made by users of IMDB service. Co-word analysis and ego-centered network analysis were adapted to discover relevant information for users who chose a specific movie. Three factors of movies including movie title, director and genre were used to present related movie information. Movie title is an effective feature to present related movies with various aspects such as theme or characters and the popularity of directors affects on identifying related directors. Genre is not useful to find related movies due to the complexity in the topic of a movie.

• Journal of the Korea Society of Computer and Information
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• v.26 no.8
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• pp.91-101
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• 2021

This paper intends to draw implications for preparing for Post-Corona in the health field and policy fields as the global pandemic is experienced due to COVID-19. The purpose of this study is to analyze the news and trends of media companies through temporal analysis of the three infectious diseases, SARS-CoV, MERS-CoV, and SARS-CoV-2 (COVID-19), in which the domestic infectious disease preventive system was active throughout the first year of the outbreak. To this end, by using the news analysis program of the Korea Press Foundation 'Big Kinds', the number of news articles per year was digitized based on the period when each infectious disease had an impact on Korea, and major trends were implemented and analyzed in a word cloud. As a result of the analysis, the number of articles related to infectious diseases peaked when the World Health Organization (WHO) declared a warning and (suspicious) confirmed cases occurred. According to keyword and word cloud analysis, 'infectious disease outbreak and major epidemic areas', 'prevention authorities', and 'disease information and confirmed patient information' were found to be the main common features, and differences were derived from the three infectious diseases. In addition, the current status of the infodemic was identified by performing word cloud analysis on information in uncertainty. The results of this study are significant in that they were able to derive the roles of the health authorities and the media that should be preceded in the event of a new disease epidemic through previously experienced infectious diseases, and areas to be rearranged.

• Journal of the Korean Wood Science and Technology
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• v.51 no.6
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• pp.458-469
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• 2023

Text mining techniques provide valuable insights into research information across various fields. In this study, text mining was used to identify research trends in wood science from 2012 to 2022, with a focus on representative journals published in Korea and Japan. Abstracts from Journal of the Korean Wood Science and Technology (JKWST, 785 articles) and Journal of Wood Science (JWS, 812 articles) obtained from the SCOPUS database were analyzed in terms of the word frequency (specifically, term frequency-inverse document frequency) and co-occurrence network analysis. Both journals showed a significant occurrence of words related to the physical and mechanical properties of wood. Furthermore, words related to wood species native to each country and their respective timber industries frequently appeared in both journals. CLT was a common keyword in engineering wood materials in Korea and Japan. In addition, the keywords "MDF," "MUF," and "GFRP" were ranked in the top 50 in Korea. Research on wood anatomy was inferred to be more active in Japan than in Korea. Co-occurrence network analysis showed that words related to the physical and structural characteristics of wood were organically related to wood materials.