• Journal of the Korea Convergence Society
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• v.6 no.5
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• pp.219-225
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• 2015

Nowadays, technologies are changing through industrial fusion and government & corporates need to predict the flow & direction of technologies. These flow & direction can be grasped through the analysis of patent information. The patent information uses the common classification codes in the world, and it is possible for the quantitative analysis based on objective data with the time information of technical area. The methods of patent analysis analyzed the technology fusion by using citation analysis & simultaneous classification analysis. This research analyzed patent information which used as an index to measure the technical innovation in the society based on knowledge, and would like to analyze technical trends and to describe the way of improvement in the future based on the aviation industry which is the representative fusion/complex industry.

• Journal of Korea Technology Innovation Society
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• v.14 no.spc
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• pp.1187-1208
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• 2011

This research aims to propose a systematic approach to identify emerging technology-product portfolio for small and medium enterprises (SMEs). Firstly, operational definition of emerging technology for SMEs is presented. Secondly, research framework is suggested and case study to show usefulness of the newly proposed framwork is analyzed. In detail, reference patent set which represent company's capabilities and business area are constructed. The research constructs patent data set for bibliometric analysis using reference patent set and citing patents to 2nd level. Clustering (expert judgement) and keyword based bibliometric approach are used. Then, cluster activity index (AI) and relevance index (RI) comparing with reference patent set are estimated. With emerging technology-product portfolio using AI and RI, a firm can identify emerging technology-product area and monitoring area.

• 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.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.3
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• pp.1-11
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• 2019

Based on the knowledge spillover theory of entrepreneurship(KSTE) and resource based view(RBV), this study examines that how patent based entrepreneurship impacts on improving key performances such as financing, firm innovation, sales, product selling growth, employment. This study which is conducted with data from 353 startup firms indicates that patent based entrepreneurship has positive effects on performance of financing, innovation, product selling growth, and employment. On the other hand, there is no effect of patent-based entrepreneurship on sales performance. This statistical results were the same The results were the same when the independent variables were measured as intensity of patent based entrepreneurship which indicates the rate of patent based product or service among total number of product or service of the startup company.

• 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.

• Proceedings of the Technology Innovation Conference
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• 1997.07a
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• pp.160-171
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• 1997

This paper starts out by reviewing the literature that in different ways utilizes patent data as a output of R&D investment. The main focus, however, is an analysis of time-lag between R&D input and output. To achieve this research objective, the basic data associated with the R&D input(expenditure, researchers) and output(patent, utilities) for the past 15 years, from 1980 to 1994, in the areas of electrical-electronic, mechanical and chemical industries have been collected. And the raw output data were altered it to objective data using Laspeyres approach and analyzed using multiple regression analysis, especially stepwise regression analysis. The result of this study can be summarized as follows: a) The time-lag between R&D input and output is from 1 to 4 years. This result is equal to the research conclusion of the existing foreign studies. b) It was found that the time-lag of patents was longer than of utility models. c) It was showed that the time-lag of electrical-electronic, mechanical industry was longer than the chemical one.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.89-97
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• 2019

This study proposes a method for investigating current patents related to information communication technology and smart mobility to provide insights into future technology trends. The method is based on text mining clustering analysis. The method consists of two stages, which are data preparation and clustering analysis, respectively. In the first stage, tokenizing, filtering, stemming, and feature selection are implemented to transform the data into a usable format (structured data) and to extract useful information for the next stage. In the second stage, the structured data is partitioned into groups. The K-medoids algorithm is selected over the K-means algorithm for this analysis owing to its advantages in dealing with noise and outliers. The results of the analysis indicate that most current patents focus mainly on smart connectivity and smart guide systems, which play a major role in the development of smart mobility.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.25-32
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• 2020

Data on patent and scientific paper is considered as a useful information source for analyzing technological information and has been widely utilized. Technology big data is analyzed in various ways to identify the latest technological trends and predict future promising technologies. Clustering is one of the ways to discover new features by creating groups from technology big data. Patent includes refined bibliographic information such as patent classification code whereas scientific paper does not have appropriate bibliographic information for clustering. This research proposes a new approach for clustering data of scientific paper by utilizing reference titles in each scientific paper. In this approach, the reference titles are considered as textual information because each reference consists of the title of the paper that represents the core content of the paper. We collected the scientific paper data, extracted the title of the reference, and conducted clustering by measuring the text-based similarity. The results from the proposed approach are compared with the results using existing methodologies that one is the approach utilizing textual information from titles and abstracts and the other one is a citation-based approach. The suggested approach in this paper shows statistically significant difference compared to the existing approaches and it shows better clustering performance. The proposed approach will be considered as a useful method for clustering scientific papers.

• KDI Journal of Economic Policy
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• v.45 no.2
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• pp.21-50
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• 2023

In this paper, I empirically estimate the relationship between digital technology and climate technology using the United States Patent and Trademark Office's patent database. I find that innovation in digital technology increases the number of patents for climate technology by 17.3% on average, with digital data-processing technology and machine-learning-related technologies especially playing a key role in this relationship. Designing and implementing detailed policies that take into account the relationship between the two technologies will help us reduce the time required to achieve carbon neutrality and shift to the digital economy.

• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.5
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• pp.901-913
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• 2017

This study analyzed the current state of art by investigating related patents of cycling wear, and suggested fundamental data to develop clothing - originated in Korea. Patent trends were then analyzed after the related patents applied in Korea, USA, and Japan from 1975 to 2015 were extracted using WIPS ON, classified as nation, applicant, technology, use, and technological maturity of the applicant country. The number of patent applications has steadily increased since the 1990s, and has steeply grown since the 2000s. The USA accounted for 55.6% of all collected patents in the study, Japan for 30.6%, and Korea for 13.7%. Technologies related to patterns and functional materials have been dominated by the USA and Japan; however, smart technologies have been actively developed in Korea. According to use, USA focused on functionality, Korea concentrated on safety, and Japan uniformly combined functionality, safety, and convenience. According to the positioning of technology by application, water repellency, stretchability, muscle strengthening, pad, panel, finishing, and weaving technologies were positioned in the functionality.