• Journal of Korea Society of Industrial Information Systems
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• v.25 no.1
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• pp.41-53
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• 2020

Supply chain management (SCM) became a critical success factor for firms. As a result, researchers have carried out related research on SCM. This study aims to explore the research trends in SCM in Korea using network text analysis. We collected the information of 586 articles published in Korean journals using the RISS database, and analyzed the network generated by keywords proposed in the articles. The results showed that there are five research keyword clusters such as logistics, information systems, partnership, risk management, and sustainability.

• Journal of the Korean Dietetic Association
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• v.22 no.4
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• pp.310-319
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• 2016

Limitation of a questionnaire survey which is widely used is time and money, limited numbers of participants, biased confidence interval and unreliable results. To overcome these, we performed tendency and network analysis of diet using big Data in Koreans. The keyword on diet were collected from the portal site Naver from January 1, 2015 until December 31, 2015 and collected data were analyzed by simple frequency analysis, N-gram analysis, keyword network analysis and seasonality analysis. The results showed that diet menu appeared most frequently by N-gram analysis, even though exercise had the highest frequency by simple frequency analysis. In addition, keyword network analysis were categorized into four groups: diet group, exercise group, commercial diet program company group and commercial diet food group. The analysis of seasonality showed that subjects' interests in diet had increased steadily since February, 2015, although subjects were most interested indiet in July, these results suggest that the best strategies for weight loss are based on diet menu and starting diet before July. As people are especially sensitive to diet trends, researches are needed about annual analysis of big data.

• Journal of the Korean Society for Library and Information Science
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• v.47 no.1
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• pp.39-55
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• 2013

It is a difficult problem to use keyword retrieval for low-quality Korean document images because these include adjacent characters that are connected. In addition, images that are created from various fonts are likely to be distorted during acquisition. In this paper, we propose and test a keyword retrieval system, using a support vector machine (SVM) for the retrieval of low-quality Korean document images. We propose a keyword retrieval method using an SVM to discriminate the similarity between two word images. We demonstrated that the proposed keyword retrieval method is more effective than the accumulated Optical Character Recognition (OCR)-based searching method. Moreover, using the SVM is better than Bayesian decision or artificial neural network for determining the similarity of two images.

• Knowledge Management Research
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• v.22 no.1
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• pp.217-242
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• 2021

The purpose of this study is to examine the research trends in the filed of individual knowledge hiding through keyword network analysis. As individuals intentionally hide their knowledge beyond not sharing their knowledge in organizations and the research on knowledge hiding steadily spreads, it is necessary to examine the research trends regarding knowledge hiding behaviors. For keyword network analyses, we collected 346 kinds of 578 keywords from 120 articles associated with knowledge hiding behaviors. We also transformed the keywords to 86 nodes and 667 links by data standardizing criteria and finally analyzed the keyword network among them. Moreover, this study scrutinized knowledge hiding trends by comparing the conceptual model for knowledge hiding based on literature review and the network structure based on keyword network analysis. As results, first, the network centrality degree, knowledge sharing, creativity, and performance was higher than others in Degree, Betweenness, Closeness centrality. Second, this study analyzed ego networks about psychological ownership and individual emotion theoretically associated with knowledge hiding and explored the relationship between variables through comparing with the conceptual model for knowledge hiding. Finally, the study suggested theoretical and practical implications and provided the limitations and suggestions for future research based on study findings.

• The KIPS Transactions:PartD
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• v.18D no.6
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• pp.501-508
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• 2011

A knowledge map, which has been recently applied in various fields, is discovering characteristics hidden in a large amount of information and showing a tangible output to understand the meaning of the discovery. In this paper, we suggested a knowledge map for research trend analysis based on keyword-relation networks which are constructed by using a database of the domestic journal articles in the computer engineering field from 2000 through 2010. From that knowledge map, we could infer influential changes of a research topic related a specific keyword through examining the change of sizes of the connected components to which the keyword belongs in the keyword-relation networks. In addition, we observed that the size of the largest connected component in the keyword-relation networks is relatively small and groups of high-similarity keyword pairs are clustered in them by comparison with the random networks. This implies that the research field corresponding to the largest connected component is not so huge and many small-scale topics included in it are highly clustered and loosely-connected to each other. our proposed knowledge map can be considered as a approach for the research trend analysis while it is impossible to obtain those results by conventional approaches such as analyzing the frequency of an individual keyword.

• Journal of the Korea Convergence Society
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• v.8 no.5
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• pp.169-178
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• 2017

In various research fields, it is important to identify the trends and meaningful patterns in large volumes of text data. We examined the research trends and patterns in global journal articles related to aviation and airlines from 1997 to 2016 using keyword network analysis. Keyword network models were constructed, and centrality (degree and betweenness) analysis was performed using 25,959 articles from the Scopus database. The results suggested that the recent research trends in aviation and airlines could be quantitatively described through keyword network analysis. The engineering and social science fields were the most relevant fields with keywords related to aviation and airlines. In addition, it was shown that betweenness centrality increased with the degree centrality of keywords. The results of this study could be applied to establish policies and suggest further research topics in the field of aviation and airlines based on empirical data.

• Journal of Industrial Convergence
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• v.18 no.2
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• pp.45-50
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• 2020

The purpose of this study is to analyze relationships among essential keywords in curriculum. The number of 1,935 keyword was collected from 644 manuscripts published between 2002 and 2019. For data analysis, this study selected softwares of KrKwic and KrTitle to compose a 1-mode network matrix and UCINET 6 and NetDraw to implement network analysis and visualization. Results are as follows. First, the frequency of keyword was curriculum, curriculum development, national curriculum, competency-based curriculum, 2015 revised national curriculum, curriculum implementation, understanding by design, competency, teacher education, school curriculum, and IBDP from highest to lowest. Second, degree centrality was curriculum development, curriculum, competency-based curriculum, national curriculum, 2015 revised national curriculum, understanding by design, competency, key competency, high school curriculum, textbook, curriculum implementation, teacher education, and IBDP from highest to lowest.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.147-148
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• 2008

현재의 자동차 전제제어 시스템에서 적용하고 있는 On-board Diagnostic system(OBD)-ll의 Diagnostic Control Network를 구성하고 있는 Keyword2000과 CAN프로토콜을 통합하여 한 시스템이 구현하고, 이에 따른 통합된 서비스를 제공하는 OBD 시스템 개발내용을 소개한다.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.278-291
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• 2016

This study examined research trends via network analyses of keywords appeared in academic research articles about news reports in South Korea during the last 10 years from 2006 to 2015. Keyword network analyses of 4410 keywords from 1108 articles suggested that framing, agenda setting, third-person effect, selective exposure, and uses and gratification were main theories but most studies used framing theory. Research areas included news reports on politics, economics, science, world issues, or tour. However, research on news reports covering culture, sports or daily life were not identified. In terms of media, research on both traditional and emerging media were ample. Research on broadcasting new, online news, and social media were frequently observed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.609-611
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• 2014

Was developed of the web service in Due to the dissemination for IT skills development and smart appliances. In particular, Social network service for should be able to communicate feel free to a user across without distinguishing between production and consumption information in contrast to the existing web service. And strengthen to the information sharing relationships between existing human relation and new human relation. In this paper, a social network service in providing a social networking from users using their communication and information sharing is used to collect and analyze in the keyword. And a design of recommended system of movies for appropriate keyword.