• Journal of Technology Innovation
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• v.25 no.3
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• pp.197-231
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• 2017

We investigate the effect of technology convergence and spillover on firm performance. In doing so we specifically examine how automobile firms adapting aircraft technologies perform in stock market and product market. In order to use technology convergence and spillover, we investigate the patent citation relationship between aircraft and automobile related patents and construct the measures on automobile firms' adaptation of aircraft technologies. We also measure automobile firms' performance based on market value of firms in the stock market and revenues in product market. We find that the market value increases as automobile firms use the knowledge of aircraft technologies more. However, there is no relationship between the use of the aircraft technology and the revenue of automobile firms. This suggests that the use of advance aircraft technology plays a positive signaling role in financial market while it is not associated with generating revenues in product market.

• Journal of Korea Technology Innovation Society
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• v.14 no.spc
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• pp.1171-1186
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• 2011

Identifying Emerging Technology Trends is crucial for decision makers of nations and organizations in order to use limited resources, such as time, money, etc., efficiently. Many researchers have proposed emerging trend detection systems based on a popularity analysis of the document, but this still needs to be improved. In this paper, an emerging trend detection classifier is proposed which uses both academic and industrial data, SCOPUS and PATSTAT. Unlike most pre-vious research, our emerging technology trend classifi-er utilizes supervised, semi-automatic, machine learning techniques to improve the precision of the results. In addition, the citation information from among the SCOPUS data is analyzed to identify the early signals of emerging technology trends.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.4
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• pp.373-397
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• 2019

Recent disasters are a complex and growing trend. In order to effectively prepare for and respond to disasters that occur without notice, it is very important to use scientific information related to disaster and safety in addition to the standardized disaster safety information that is used. In this paper, we searched and selected major journals in the field of disaster & safety and conducted various network analysis studies using the classification scheme for development of integrated metadata for disaster & safety information developed through Disaster & Safety Information Sharing Platform R&D project as well as KSCD. Also, we have constructed and analyzed citation network, co-authorship network and keyword network through data identification and preprocessing of research paper contents. As a result of this study, based on the network constructed by information analysis unit, the network structure between core domestic and foreign journals, major research institutes, core keywords and individual information by disaster & safety type was identified in detail, and the analysis results were presented on a case-by-case basis.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.351-357
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• 2021

At the time when interest in the use of big data is rising in the face of the technological paradigm shift of the 4th industrial revolution, interest in the use of patented big data is increasing, especially as the proportion of intangible assets of companies increases. In addition to quantitative information, patent data contains various information such as unstructured text such as title, abstract, claim, citation and citation relations, drawings, and technology classification. It is judged that the use of treatment is important. Therefore, in this study, in order to systematically operate the innovative patent strategy framework and to secure a competitive advantage by strengthening the fundamental technological competitiveness of the company, we propose a method of using patent big data centering on the case of Company A, and verify its validity. I would like to suggest some implications. Through this, it is intended to raise awareness of the use of patent big data, and to suggest ways to use patent big data in connection with the company's company-wide strategy, business strategy, and functional strategy.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.4
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• pp.139-157
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• 2022

Finding and selecting proper reviewers is a burden on the publisher of the journal. In order to solve this problem, the online submission system started to recommend appropriate reviewers automatically. It includes a variety of new features, from recommending authors in the references of submitted papers as reviewers to finding similar papers by searching the citation index and suggesting reviewer candidates extensively. This study investigated how the online submission system provides functions such as recommendation of reviewers. As a result of examining major online submission systems, ScholarOne and Editorial Manager were recommending reviewer candidates by commercial citation index and review history platform. On the other hand, JAMS, a domestic online submission system, did not have any advanced functions such as recommendation of candidates for reviewers. Sooner or later, in Korea, it seems that more efforts should be made to improve the function of online submission system, such as recommending suitable reviewers for papers.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.283-295
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• 2022

The number of citations in a patent is one of the indicators of the qualitative value of a patent. In this study, negative binomial regression model analysis was performed focusing on 47,354 US patents of 14 global top automotive makers in order to examine the major factors affecting the number of patent citations. As a result of the review, it was found that, elapsed years since filing, the number of patent claims, the number of claim letters, the number of inventors, the number of patent family countries, and the number of patent families, as well as IPC diversity, had a positive and significant effect on the number of citations. The results of this study are expected to provide a basic basis for considering the IPC diversity index together in analyzing and evaluating future patents and establishing strategies for creating excellent patents.

• The Journal of Information Systems
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• v.23 no.3
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• pp.127-142
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• 2014

Plagiarism occurs when the content is copied without permission or citation, and the problem of plagiarism has rapidly increased because of the digital era of resources available on the World Wide Web. An important task in plagiarism detection is measuring and determining similar text portions between a given pair of documents. One of the main difficulties of this task is that not all similar text fragments are examples of plagiarism, since thematic coincidences also tend to produce portions of similar text. In order to handle this problem, this paper proposed association analysis in data mining to detect plagiarism. This method is able to detect common actions performed by plagiarists such as word deletion, insertion and transposition, allowing to obtain plausible portions of plagiarized text. Experimental results employing an unsupervised document classification strategy showed that the proposed method outperformed traditionally used approaches.

• Journal of Information Science Theory and Practice
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• v.2 no.4
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• pp.20-30
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• 2014

This study examines the foremost concerns related to most noted research performance index. The most popular and widely acceptable h-index underestimates the highly visible scientist, the middle order group, due to citation distribution issues. The study addresses this issue and uses 'Corrected Quality Ratio' (CQ) to check the implicit underpinnings as evident in h-index. CQ helps to incorporate the aspects of a good research performance indicator. This simple revision performs more intimately and logically to gauge the broader research impact for all groups and highly visible scientists with less statistical error.

• Journal of Contemporary Eastern Asia
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• v.17 no.2
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• pp.237-253
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• 2018

In order to understand China's internet governance, this paper examined 1,931 Internet policies of China by bibliometric techniques. Specifically, the bibliometric techniques include simple document counting, co-word analysis, collaboration network analysis and citation analysis. The findings include: (1) China's Internet legislations mainly emphasized e-commerce and Internet governance, and, to some extent, neglected personal data protection; (2) China's Internet is under intensive multiple regulatory controls by central government. A large number of government agencies are involved in Internet policy-making. The Propaganda Department of the Central Committee of the Communist Party of China and the State Information Leading Group of the State Council, enforced fewer policy documents, but occupy higher positions in the Internet governance hierarchy; (3) China's Internet legislation system is primarily composed of industry-specific administrative rules, rather than laws or administrative regulations. Nevertheless, laws and administrative regulations received significantly more citations owing to their superior force. This paper also discussed current gaps in China's internet governance and how the country's internet policies are situated in the broader global context.

• Journal of Fisheries and Marine Sciences Education
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• v.29 no.1
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• pp.224-233
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• 2017

This study aims to analyze the research trend of lifelong education in Korea over the last 10 years based on social network analysis. To do this, a dataset has been collected from KCI (Korea Citation Index) database. According to the results of the study, firstly, the current status of lifelong education research by the year in the last 10 years showed a relatively high ratio between 2008 and 2009 and 2014 ~ 2015. Secondly, the most active networks between authors and journals constitute a key group in the order of 'Lifelong Education Study' and 'Lifelong Learning Society'. Thirdly, the research institutes with the largest number of lifelong education research papers are Soongsil University, Dong-Eui University, and Korea National Open University. In the network with the authors' network, the only authors were K8 working at Chonbuk National University, and the co-authors, H4, who works at Kyungpook National University, showed the most active network. Finally, the core keyword network based on the thesis topic was analyzed as having higher connection centrality in the order of 'lifelong education', 'lifelong educator', and 'university lifelong education'.