• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.107-114
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• 2020

Technologies related scan-to-BIM for BIM-based reverse engineering techniques are beginning to be actively introduced in the A.E.C. industry, and the scalability of the technology is growing considerably. This study uses patent analysis based on objective data to find the right direction for Korean Scan-to-BIM technology by identifying the trends in Korea, the United States, Europe, and Japan. This was done using the WIPSON patent search system to find previous research on patent analysis related to building technology, theoretical consideration of scan-to-BIM technology, and published patents. We collected information, verified the process, and extracted valid patents. We used the effective patent data to analyze the annual trend of patent applications, national trends, and technological trends through the International Patent Classification (IPC) code, the types of the top 20 major applicants, and family patent trends.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.3
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• pp.156-169
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• 2016

The objective of this study is to investigate patent trends of Daegu city which tries to introduce environment friendly energy and to develop new technology or new industry sprung from technology convergence on smart decentralized energy technology and other technologies. After applying network analysis to corresponding groups of technology or industry convergence, strategy for future energy convergence industry is provided. Patent data applied in Daegu city area are used to obtain research goal. The technology which contains several IPC codes (IPC Co-occurrence) is considered as a convergence technology. Path finder network analysis is used for visualizing and grouping by using IPC codes. The analysis results categorized 13 groups in energy convergence industry and reclassified them into 3 cluster groups (Smart Energy Product Production Technology Group, Smart Energy Convergence Supply Technology Group, Smart Energy Indirect Application Technology Group) considering the technical characteristics and policy direction. Also, energy industry has evolved rapidly by technological convergence with other industries. Especially, it has been converged with IT industry, and there is a trend that energy industry will be converged with service industry and manufacturing industry such as textile, automobile parts, mechanics, and logistics by employing infrastructure as well as network. Based on the research results on core patent technology, convergence technology and inter-industry analysis, the direction of core technology research and development as well as evolution on decentralized energy industry is identified. By using research design and methodology in this study, the trend of convergence technology is investigated based on objective data (patent data). Above all, we can easily confirm the core technology in the local industry by analyzing the industrial competitiveness in the macro level. Based on this, we can identify convergence industry and technology by performing the technological convergence analysis in the micro level.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.88-95
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• 2017

As the safety fields are expanding to a variety of industrial fields, safety technology has been developed by convergence between industrial safety fields such as mechanics, ergonomics, electronics, chemistry, construction, and information science. As the technology convergence is facilitating recently advanced safety technology, it is important to explore the trends of safety technology for understanding which industrial technologies have been integrated thus far. For studying the trends of technology, the patent is considered one of the useful sources that has provided the ample information of new technology. The patent has been also used to identify the patterns of technology convergence through various quantitative methods. In this respect, this study aims to identify the convergence patterns and fields of safety technology using association rule mining(ARM)-based patent co-classification(co-class) analysis. The patent co-class data is especially useful for constructing convergence network between technological fields. Through linkages between technological fields, the core and hub classes of convergence network are explored to provide insight into the fields of safety technology. As the representative method for analyzing patent co-class network, the ARM is used to find the likelihood of co-occurrence of patent classes and the ARM network is presented to visualize the convergence network of safety technology. As a result, we find three major convergence fields of safety technology: working safety, medical safety, and vehicle safety.

• The Journal of the Korea Contents Association
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• v.9 no.2
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• pp.125-132
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• 2009

The paradigm of economy has been transformed into knowledge based economic paradigm in 21th century. Analysis of patent trend is one of the strategic methods for increasing their patent competitive power. However, this method is just presenting statistical data about patent trend or qualitative analysis about some core technology. In this paper, we forecast technology diffusion using patent information for more progressive analysis. We make an experiment with bass model and logistic model and make use of patent data about information-security technology for NCW as input data. We conclude that the logistic model is more efficient for forecasting and this technology is approaching to the age of technology maturity.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.355-360
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• 2014

Forecasting of emerging technology plays important roles in business strategy and R&D investment. There are various ways for technology forecasting including patent analysis. Qualitative analysis methods through experts' evaluations and opinions have been mainly used for technology forecasting using patents. However qualitative methods do not assure objectivity of analysis results and requires high cost and long time. To make up for the weaknesses, we are able to analyze patent data quantitatively and statistically by using text mining technique. In this paper, we suggest a new method of technology forecasting using text mining and ARIMA analysis.

• Journal of Technology Innovation
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• v.12 no.1
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• pp.1-24
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• 2004

This paper analyses the effects of R＆D investment on patent in Korean manufacturing firms during the period 1984-99. The data contains 140 companies which listed in Korea Stock Exchange(KSE). We observed that the relative shares of R＆D investments and patent applications are much higher in scientific firms than in the other firms. The regression results show that R＆D investment has significantly positive effects on the growth of patent application and registration. And the effects of R＆D on patent turns out to be stronger in scientific firms than the other firms. The firm size and the capital intensity also have an important effect on the propensity to patent.

• Journal of Korea Technology Innovation Society
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• v.19 no.2
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• pp.280-301
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• 2016

The competition environment among companies is rapidly expanding into the world market. Therefore, this study intended to suggest an analysis method of patent portfolio that can compare an international technological capacity through empirical analysis on the global automobile companies. This study measured international patent activity using triadic patent data of 20 years from 1991 to 2010, and measured patent quality from legal, technological and economic aspects. As a result, Ford and GM, automobile companies of America, are analyzed to be the potential leaders with greatly increased patent quality. The significance of this study is in measuring international patent activities between global companies from different countries based on the triadic patent. And, this study suggested methods of analyzing patent quality consistently from legal, technological and economic aspects based on the triadic patent.

• Journal of the Korean Society of Radiology
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• v.13 no.5
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• pp.785-790
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• 2019

Convergence and advancement between technologies such as Artificial Intelligence, Big Data, and the Internet of Things have a significant impact on the regional flagship industry. All technical fields are used as a converged technology by connecting between technology and industry. In order to understanding the recent technical trend, it is possible to easily realized the technical trend research and analysis through keyword search using patent information. The purpose of this study is to identify patent trends applied to convergence technology in the 4th Industrial Revolution age in radiation technology development and to present patent trends and analysis for strengthening and utilizing radiation-related industrial technology competitiveness and to apply them to demand technology and forecast future promising technologies.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.165-172
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• 2017

In this paper, we analyze the research / technology trends of electric vehicles from 2001 to 2014, through keyword analysis using paper data published in SCIE or SSCI Journal on electric vehicles, time series analysis using patent data by IPC, and network analysis using nodeXL. also we predicted promising technologies of electric vehicles using one of the prediction methods, weighted moving average method. As a result of this study, battery technology among the electric vehicle component technologies appeared as a promising technology.

• Journal of Korea Technology Innovation Society
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• v.19 no.2
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• pp.254-279
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• 2016

Recently, with the conversion towards knowledge-based economy era, the importance of the evaluation for patent valuation has been growing rapidly because technology transactions are increasing with the purpose of practically utilizing R&D outcomes such as technology commercialization and technology transfer. Nevertheless, there is a lack of research on determinants of patent valuation by analyzing technology transactions due to the difficulty of collecting data in practice. Hence, to suggest quantitative determinants for the patent valuation which could be applied to scoring methods, 15 patent valuation models domestically and overseas are analysed in order to assure the objectiveness for subjective results from qualitative methods such as expert surveys, comparison assessment, etc. Through this analysis, the important 6 common determinants are drawn and patent information is matched which can be used as proxy variables of individual determinant factors by advanced researches. In addition, to validate whether the model proposed has a statistically meaningful effect, total 517 technology transactions are collected from both public and private technology transaction offices and analysed by multiple regression analysis, which led to significant patent determinant factors in deciding its value. As a result, it is herein presented that patent connectivity(number of literature cited) and commercialization stage in market influence significantly on patent valuation. The meaning of this study is in that it suggests the significant quantitative determinants of patent valuation based on the technology transactions data in practice, and if research results by industry are systematically verified through seamless collection of transaction data and their monitoring, we would propose the customized patent valuation model by industry which is applicable for both strategic planning of patent registration and achievement assessment of research projects (with representative patents).