• 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.25 no.4
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• pp.211-238
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• 2017

This study was conducted using social network analysis, variance analysis, and regression analysis to investigate the effects of cooperation between innovators on technical performance. Based on data of joint applicants filed with the Korean Intellectual Property Office from 2009 to 2012, we derive network structural variables and characteristic variables, and identify network characteristics that affect the overall network structural type, roles for each subject of innovation, and innovation performance. The findings are as follows: ⅰ) The network of this study is a distributed, small-world network within which relatively small groups of innovators are distributed. ⅱ) Universities were found to play the most important role in cooperation, but diversity of cooperating partners exhibited similar effects. ⅲ) It was shown that access to quick and accurate knowledge from familiar partners exhibits a more positive influence on generating innovative performance than unfamiliar knowledge from a variety of cooperating partners in non-familiar fields.

• Asian Journal of Innovation and Policy
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• v.5 no.3
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• pp.293-314
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• 2016

Patent information as a proxy measure of technological capability has been utilized to establish technological strategies of firms. It is important to monitor what competitors' plans for direction on research and development in the initial stage of new industry. Cancer metabolism has been considered as a beacon of hope for cancer research because it is anticipated that the research field will play a central role in developing effective cancer therapies. There is little attention given to understanding the status quo of organizational configurations. By utilizing network analysis, six sub-groups of cancer metabolism were categorized and the relationship between an individual field and participants were analyzed based on cluster and entire network-level. Although the largest drug and biotech companies tried to take an initiative across the whole fields, the differences in technological capabilities between them was discovered. This paper attempts to improve the validity of the suggested procedure and is significant in that it looks at the entire structure of cancer metabolism research from a strategic perspective for the first time.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.3
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• pp.471-481
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• 2023

Digital twin is considered as a key technology of industry 4.0, thus being essential for the future of industrial production. Despite the significance, a systematic analysis of its technological landscape is lacking. This study aims to investigate the technological development trends and newly emerging technological convergence opportunities in the domain of digital twin by exploiting patent information derived from U SPTO. For this purpose, this study visualized and predicted the convergence dynamics among patent classification codes by adopting patent co-classification analysis and link prediction approach. The findings show that the number of digital twin-related patent applications has increased significantly since 2018. The CPC code G06F showed the highest eigenvector centrality, while G05B was characterized by highest betweenness centrality. According to the predictive model, 41 novel links were revealed, acting as potential technology convergence opportunities. These links were then categorized into 11 different domains. The most dominant category was "digital data processing and artificial intelligence", which could play a foundational role in the diffusion of digital twin technology. The presence of digital twin technology is dominant in manufacturing, but its applications are expected to expand, including "climate change", "healthcare" and "aerospace engineering". The derived insights can support R&D managers and policy makers in formulating R&D strategies and directing future R&D investment decisions.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.107-115
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• 2013

Various networks can be observed in the world. Knowledge networks which are closely related with technology and research are especially important because these networks help us understand how knowledge is produced. Therefore, many studies regarding knowledge networks have been conducted. The assortativity coefficient represents the tendency of connections between nodes having a similar property as figures. The relevant characteristics of the assortativity coefficient help us understand how corresponding technologies have evolved in the keyword-based patent network which is considered to be a knowledge network. The relationships of keywords in a knowledge network where a node is depicted as a keyword show the structure of the technology development process. In this paper, we suggest two hypotheses basedon the previous research indicating that there exist core nodes in the keyword network and we conduct assortativity analysis to verify the hypotheses. First, the patents network based on the keyword represents disassortativity over time. Through our assortativity analysis, it is confirmed that the knowledge network shows disassortativity as the network evolves. Second, as the keyword-based patents network becomes disassortavie, clustering coefficients become lower. As the result of this hypothesis, weconfirm the clustering coefficient also becomes lower as the assortative coefficient of the network gets lower. Another interesting result concerning the second hypothesis is that, when the knowledge network is disassorativie, the tendency of decreasing of the clustering coefficient is much higher than when the network is assortative.

• Journal of Information Technology Applications and Management
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• v.28 no.4
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• pp.79-101
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• 2021

The purpose of this research is to define detailed technologies of smart city based on excellent patents through patent analysis related to major technologies of smart city, and to use quantitative indicators to classify relatively high technology importance and identify related technologies. To achieve the purpose of the study, patent collection is conducted by reflecting literature research and expert opinions based on information related to the smart city Internet of Things/Internet of Things communication core technology. Also, DEA were used to determine the relatively high technology. The inputs and outputs used in the study used quantitative indicators to determine technical value and made up of impact assessment, performance assessment and value assessment. As a result of the analysis, various technology groups were classified into smart city-related platform technologies, information sharing technologies, and network-related technologies, and based on the results of this research, it is expected that it will be able to apply technology patents related to smart cities to research and development strategies through key detailed technologies by major technologies of Smart City.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.85-93
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• 2019

Despite its matchless position in the global semiconductor industry, Korea has not distinguished itself in the semiconductor equipment sector. Semiconductor cleaning equipment is one of the semiconductor fabrication equipment, and it is expected to be more important along with the advancement of semiconductor fabrication processes. This study attempts to analyze technology competitiveness of major countries in the sector including Korea, and explore specialty sub-areas of the countries. For this purpose, we collected patents of semiconductor cleaning equipment during the last 10 years from the US patent database, and implemented quantitative patent analysis and co-classification network analysis. The result shows that, the US and Japan have been leading the technological progress in this sector, and Korea's competitiveness has lagged behind not only the leading countries but also its competitors and even latecomers. Therefore, intensive R&D and developing technological capabilities are needed for advancing the country's competitiveness in the sector.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.261-270
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• 2020

In this study, we identify promising technologies for Piggyback transportation system by analyzing the relevant patent information. In order for this, we first develop the patent database by extracting relevant technology keywords from the pioneering research papers for the Piggyback flactcar system. We then employed textmining to identify the frequently referred words from the patent database, and using these words, we applied the LDA (Latent Dirichlet Allocation) algorithm in order to identify "topics" that are corresponding to "key" technologies for the Piggyback system. Finally, we employ the ARIMA model to forecast the trends of these "key" technologies for technology forecasting, and identify the promising technologies for the Piggyback system. with keyword search method the patent analysis. The results show that data-driven integrated management system, operation planning system and special cargo (especially fluid and gas) handling/storage technologies are identified to be the "key" promising technolgies for the future of the Piggyback system, and data reception/analysis techniques must be developed in order to improve the system performance. The proposed procedure and analysis method provides useful insights to develop the R&D strategy and the technology roadmap for the Piggyback system.

• Journal of the Economic Geographical Society of Korea
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• v.19 no.3
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• pp.474-490
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• 2016

This paper investigates how Kora steel industry has experienced technological diversification, organizational flexibility, and geographical dispersion, and analyzes how technology-knowledge network has formed. The network is constructed using mutual patent data. K-medoid clustering and brokerage analysis are applied. The results indicate actors in network are diversified and links between those who belong to the same cluster get stronger. Network formation reflects affiliation, competition, and cooperation in the industry, and brokerage roles of conglomerates, research institute, and small and medium sized companies are detected.

• Journal of Technology Innovation
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• v.27 no.4
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• pp.1-19
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• 2019

This study presents a new method to evaluate patents by public R&D program using patent citation network analysis. I used forward citation, degree centrality, betweenness centrality and page rank as the dependent variables which represents the quality of patents. I used primary independent variable as a dummy of public R&D program and controlled patents characteristics, applicant characteristics, technological characteristics and year effect. The empirical result shows that the patents of public R&D program is superior to other patents in regard to the number of forward citation, the degree centrality, the betweenness centrality and the page rank. This empirical result implies that patents of public R&D program directly and effectively connects technologies. Also patents from public R&D program connects important technologies.