• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2724-2730
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• 2015

Internet of Things (IoT) is possibly the most widely discussed technological concept in today's technology circles. This technology is expected to dramatically change not only how we work but also how we live. The concept of IoT basically means a web of connected devices which can be controlled over a data network. With cost of technology required to control these devices going down and increasing internet connectivity through smartphones, IoT is expected to be an all pervasive technology in the next 10 years. In this paper, we study the technological landscape of this fast growing technology domain from an Intellectual Property (Patents) perspective. We find that the patent distribution in this domain is very fragmented with the top patent applicants in the field holding around 5% of the total patents. Especially, the US geography has seen the maximum patent filings and is closely followed by the big Asian markets of Japan and Korea.

• Journal of Information Technology Applications and Management
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• v.21 no.4
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• pp.65-96
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• 2014

To have global competitiveness in newly growing industry, good quality R&D's in convergence technology arerequired. Korean government also started to emphasize the importance of convergence technology as a new engine of growth for the future development. Since 2008, worldwide energy crisis and concerns on low carbon green growth made people focus on the convergence between information technology (IT) and energy technology (ET). However, the R&D performance comparison among the convergence technologies is not well explored so far. Therefore, this study uses Korea's patent citation database to measure the R&D performance of convergence technologies. We adopt technology development cycle, technology spillover analysis, and technology diffusion analysis to see the knowledge flow from R&D industry to others. We find that IT_ET convergence technology generally shows higher R&D performance than other convergence technologies. Contrary to public belief, convergence R&D by big companies has relatively low performance especially measures in technology spillover and technology diffusion. This implies that they might concentrate on delicate Fuel Cell Energy/Environment Technology (FEIT) or Nano Environment/Energy Information Technology (NEIT) rather than general energy information technologies. We also find that Korea's chemical industry may play a crucial role for the growth of other convergence technologies.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1025-1039
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• 2016

We introduce various methods to investigate the relations between innovation of technology and social changes by analyzing more than 4 millions of patents registered at United States Patent and Trademark Office(USPTO) from year 1985 to 2015. First, we review the history of patent law and its relation with the quantitative changes of registered patents. Second, we investigate the differences of technical innovations of several countries by use of cluster analysis based on the numbers of registered patents at several technical sectors. Third, we introduce the PageRank algorithm to define important nodes in network type data and apply the PageRank algorithm to find important technical sectors based on citation information between registered patents. Finally, we explain how to use the canonical correlation analysis to study relationship between technical innovation and social changes.

• Journal of Technology Innovation
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• v.11 no.2
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• pp.1-25
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• 2003

Korean technological innovation is characterized by large firm-leading and characterized sector such as electricity and electronics. We examine the relationship between two elements. Using patent data registered at USPTO by Korean firms, We examine the relationship between patterns of innovative activities and sectoral specialization. As a result, Korean technological innovation is characterized by relatively high asymmetry, big share of large firms, high stability of ranking of innovators and diminishing role of newcomer, therefore as close as Schumpeter Mark II. But technological specialization is associated positively with the big share of large firms, negatively with low stability of ranking of innovators. It means that Korean technological innovation is led by large firms, but quantitative growth and technological specialization is achieved through competition between them.

• Journal of Information Technology Applications and Management
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• v.29 no.6
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• pp.1-12
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• 2022

In recent years, technological competition in the automobile sector is accelerating. This study analyzes the status of patents from a global perspective of three promising future items that Korea has selected as core technologies in the field of autonomous driving,. And the technological cooperation ecosystem was identified through network analysis centered on scientific metrology. As a result of the analysis, it was confirmed that the growth of individual technologies has been strengthened in recent years, and although key source technologies have been largely preempted in major global countries, a close cooperative ecosystem between institutions, companies, and universities in major countries has not yet been formed. Specifically, the US and Japan have the technological leadership, while China is rapidly rising, and Korea is chasing after it as a latecomer. Therefore, it is necessary to continuously strengthen technological cooperation such as R&D of core technology to overcome technological limitations and strengthening of infrastructure construction, attracting excellent foreign talents and international exchanges. This analysis is meaningful in that it explores the global status of Korea's technology and the possibility of technological cooperation from various perspectives in the future from the viewpoint of preoccupation of future technology, rather than grasping the trend of a specific technology.

• Journal of Industrial Convergence
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• v.21 no.10
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• pp.21-28
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• 2023

As the need for the use of big data increases, various analysis activities using big data, including SNS data, are being carried out in individuals, companies, and countries. However, existing research on predicting technology market trends has been mainly conducted using expert-dependent or patent or literature research-based data, and objective technology prediction using big data is needed. Therefore, this study aims to present a model for predicting future technologies through decision tree analysis, visualization analysis, and percentage analysis with data from social network services (SNS). As a result of the study, percentage analysis was better able to predict positive techniques compared to other analysis results, and visualization analysis was better able to predict negative techniques compared to other analysis results. The decision tree analysis was also able to make meaningful predictions.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.127-139
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• 2013

With an advent of recent knowledge-based society, the interest in intellectual property has increased. Firms have tired to result in productive outcomes through continuous innovative activity. Especially, ICT firms which lead high-tech industry have tried to manage intellectual property more systematically. Firm's interest in the patent has increased in order to manage the innovative activity and Knowledge property. The patent involves not only simple information but also important values as information of technology, management and right. Moreover, as the patent has the detailed contents regarding technology development activity, it is regarded as valuable data. The patent which reflects technology spread and research outcomes and business performances are closely interrelated as the patent is considered as a significant the level of firm's innovation. As the patent information which represents companies' intellectual capital is accumulated continuously, it has become possible to do quantitative analysis. The advantages of patent in the related industry information and it's standardize information can be easily obtained. Through the patent, the flow of knowledge can be determined. The patent information can analyze in various levels from patent to nation. The patent information is used to analyze technical status and the effects on performance. The patent which has a high frequency of citation refers to having high technological values. Analyzing the patent information contains both citation index analysis using the number of citation and network analysis using citation relationship. Network analysis can provide the information on the flows of knowledge and technological changes, and it can show future research direction. Studies using the patent citation analysis vary academically and practically. For the citation index research, studies to analyze influential big patent has been conducted, and for the network analysis research, studies to find out the flows of technology in a certain industry has been conducted. Social network analysis is applied not only in the sociology, but also in a field of management consulting and company's knowledge management. Research of how the company's network position has an impact on business performances has been conducted from various aspects in a field of network analysis. Social network analysis can be based on the visual forms. Network indicators are available through the quantitative analysis. Social network analysis is used when analyzing outcomes in terms of the position of network. Social network analysis focuses largely on centrality and structural holes. Centrality indicates that actors having central positions among other actors have an advantage to exert stronger influence for exchange relationship. Degree centrality, betweenness centrality and closeness centrality are used for centrality analysis. Structural holes refer to an empty place in social structure and are defined as efficiency and constraints. This study stresses and analyzes firms' network in terms of the patent and how network characteristics have an influence on business performances. For the purpose of doing this, seventy-four ICT companies listed in S&P500 are chosen for the sample. UCINET6 is used to analyze the network structural characteristics such as outdegree centrality, betweenness centrality and efficiency. Then, regression analysis test is conducted to find out how these network characteristics are related to business performance. It is found that each network index has significant impacts on net income, i.e. business performance. However, it is found that efficiency is negatively associated with business performance. As the efficiency increases, net income decreases and it has a negative impact on business performances. Furthermore, it is shown that betweenness centrality solely has statistically significance for the multiple regression analysis with three network indexes. The patent citation network analysis shows the flows of knowledge between firms, and it can be expected to contribute to company's management strategies by analyzing company's network structural positions.

• Convergence Security Journal
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• v.15 no.4
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• pp.27-33
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• 2015

In this paper, the development level of information security technology for internet of things(Iot), big data and clo ud services is analyzed, and the detail policy is proposed to be leader in area of patents and ICT standard. The conc ept of ICT convergence is defined frist, market and current state of technology for three convergence services is the n analyzed, and finally main function and security target for each technology are presented. The evaluation criteria a nd IPR are analyzed to diagnose the level of patent and standard for the technology. From the results, even though the domestic competence is inferior compared to other advanced country, the efficient policy should be presented by using our capability for the big data and cloud. Furthermore, the technology development for the IoT and cloud is ne eded in advance considering the market-technology influence effects. In addition to, M2M security framework in IoT, data security in big data and reliable networking in cloud should be developed in advance.

• Journal of Information Technology Applications and Management
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• v.31 no.1
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• pp.139-161
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• 2024

The Fourth Industrial Revolution has spurred widespread adoption of AI-based services, driving global interest in AI semiconductors for efficient large-scale computation. Text mining research, historically using LDA, has evolved with machine learning integration, exemplified by the 2021 BERTopic technology. This study employs BERTopic to analyze AI semiconductor-related patents and research data, generating 48 topics from 2,256 patents and 40 topics from 1,112 publications. While providing valuable insights into technology trends, the study acknowledges limitations in taking a macro approach to the entire AI semiconductor industry. Future research may explore specific technologies for more nuanced insights as the industry matures.

• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.233-239
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• 2021

Recently, the COVID-19 virus has caused people to stay indoors longer without going out. As a result of this, people's activity decreased sharply, and their weight gained. So people became more interested in health. Home training can be an alternative method to solve this problem. Accordingly, To find out the trends of home training, we collected articles from December 1, 2019, to November 30, 2020, using the news provided by BIG KINDS, a news analysis system. We analyzed frequency analysis, relational analysis according to weighting, and related word analysis with the program using the algorithm developed by BIG KINDS. In conclusion, first, it was found that home training is led by technology and the emergence of artificial intelligence. Second, it can be assumed that people mainly do home training using content and video services related to mobile carriers. Third, people had a high preference for Pilates in the sports category. It can be seen that the number of patent applications increased as the demand for exercise products related to Pilates increased. In the next study, we expect that this study will be used as primary data for various big data studies by supplementing the research methodology and conducting various analyses.