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

• The Korean Journal of Applied Statistics
• /
• v.29 no.4
• /
• pp.613-625
• /
• 2016

The development of technology has changed the world drastically. Patent data analysis helps to understand modern technology trends and predict prospective future technology. In this paper, we analyze the patent citation network using the USPTO data between 1985 and 2012 to identify technology trends. We use network centrality measures that include a PageRank algorithm to find core technologies and identify groups of technology with similar properties with statistical network models.

• Journal of the Korea Convergence Society
• /
• v.9 no.12
• /
• pp.17-24
• /
• 2018

This study attempted to analyze technology convergence structure and key technology research sectors in bio-health. For this, network analysis was performed based on the patent outcomes achieved through national R&Ds. Then, a patent network was analyzed to derive problems and collect data from the National Science & Technology Information Service. With the five groups obtained through the analysis of IPC network and national R&D patents in bio-health based on a research frame network, topics were chosen based on the bio-healthcare technology system. Then, the technology with the greatest ripple effects was derived and compared to other sectors, suggesting a direction for national R&D investments. It is anticipated that this study would make a contribution to a search for R&D investment direction by additionally analyzing overseas patent data and improving correlation analysis between technology convergence and government-led R&D expenses.

• Journal of the Semiconductor & Display Technology
• /
• v.18 no.1
• /
• pp.105-111
• /
• 2019

The TADF (Thermally Activated Delayed Fluorescence)-based OLED patents were analyzed and 4410 of patents were selected at the first step. And 975 patents were screened at second step. Finally, 39 key patents were selected. Patent qualitative analysis was performed in these patents to find which of the four property (lifetime, efficiency, color purity, driving voltage) of TADF was improved. Also, the variation of the hosts and dopants in patented TADF material were surveyed and their combination was analyzed. According to the analysis of the variation and the combination, some of TADF compounds were used as an assistant dopant to transfer energy. In addition, it tended to transfer energy by forming exciplex that shows TADF characteristics. These were similar to the mechanism of the introduced hyper fluorescence and could solve the inherent TADF problems. Finally, patent citation network was illustrated to visualize the patent citations and citations relationship of the major applicants in the current TADF-based OLED technology. The leading patent applicant organization was revealed as Idemitsu Kosan, Semiconductor Energy Laboratory, UDC, Princeton University, Merck and Nippon Steel & Sumikin Chemical, which had lots of reference patents 559, 524, 477, 310, 258, and 167, respectively.

• Journal of Technology Innovation
• /
• v.25 no.3
• /
• pp.1-24
• /
• 2017

With the rise of internet of things (IoT), there have been several studies to analyze the technological trend and technological convergence. However, previous work have been relied on the qualitative work that investigate the IoT trend and implication for future business. In response, this study considers the patent information as the proxy measure of technology, and conducts a quantitative and analytic approach for analyzing technological convergence using patent co-classification analysis and text mining. First, this study investigate the characteristics of IoT business, and characterize IoT business into four dimensions: device, network, platform, and services. After this process, total 923 patent classes are classified into four types of IoT technology group. Since most of patent classes are classified into device technology, we developed a co-classification network for both device technology and all technologies. Patent keywords are also extracted and these keywords are also classified into four types: device, network, platform, and services. As a result, technologies for several IoT devices such as sensors, healthcare, and energy management are derived as a main convergence group for the device network. For the total IoT network, base network technology plays a key role to characterize technological convergence in the IoT network, mediating the technological convergence in each application area such as smart healthcare, smart home, and smart grid. This work is expected to effectively be utilized in the technology planning of IoT businesses.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.23 no.3
• /
• pp.315-325
• /
• 2015

Smart Car market has been experiencing continuous growth to drive leading companies in automotive and IT industries to focus on advancing related technologies. As the IT technologies fuse into automotive technologies, the patent litigation has been showing changes. One of the prominent changes in patent litigation pattern of Smart Car field is the increased activities of the Non-Practicing Entities (NPEs), whose main field has been the IT area. However, the automotive companies have been mainly focusing on preventing patent disputes against competitors through trend analysis, which caused them to become relatively vulnerable to the attacks from NPEs. In this study, we developed a methodology for monitoring and analyzing the activities of NPEs using network analysis tools to suggest effective strategies for manufacturing companies to fortify their ability to respond against unanticipated attacks. Our methodology, which is developed for the Smart Car field, can also be useful for other fields such as IT and electronics.

• Journal of the Korea Safety Management & Science
• /
• v.16 no.1
• /
• pp.213-220
• /
• 2014

This study suggests new approach to identify core technologies through patent analysis. Specially, the approach applied data mining technique and multi-criteria decision making method to the co-classification information of registered patents. First, technological interrelationship matrices of intensity, relatedness, and cross-impact perspectives are constructed with support, lift and confidence values calculated by conducting an association rule mining on the co-classification information of patent data. Second, the analytic network process is applied to the constructed technological interrelationship matrices in order to produce the importance values of technologies from each perspective. Finally, data envelopment analysis is employed to the derived importance values in order to identify priorities of technologies, putting three perspectives together. It is expected that suggested approach could help technology planners to formulate strategy and policy for technological innovation.

• Journal of the Korean Data and Information Science Society
• /
• v.27 no.5
• /
• pp.1273-1284
• /
• 2016

In this paper, we analyzed the patents on machine learning using keyword network analysis and clique analysis. To construct a keyword network, important keywords were extracted based on the TF-IDF weight and their association, and network structure analysis and clique analysis was performed. Density and clustering coefficient of the patent keyword network are low, which shows that patent keywords on machine learning are weakly connected with each other. It is because the important patents on machine learning are mainly registered in the application system of machine learning rather thant machine learning techniques. Also, our results of clique analysis showed that the keywords found by cliques in 2005 patents are the subjects such as newsmaker verification, product forecasting, virus detection, biomarkers, and workflow management, while those in 2015 patents contain the subjects such as digital imaging, payment card, calling system, mammogram system, price prediction, etc. The clique analysis can be used not only for identifying specialized subjects, but also for search keywords in patent search systems.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.4
• /
• pp.382-390
• /
• 2019

As there is severe competition in the global foldable display market, strategic technology planning is required. Patent analysis as a tool for technology planning has frequently been used due to data characteristics such as openness, formality, and detailed information. However, traditional patent analysis has various limitations such as quantitative approaches are limited in evaluating contents of patents and identifying core technologies of firms as they rely on number of patents, and qualitative approaches have time and cost problems as researchers have to investigate each patent on a case-by-case basis. In this research, we analyze core technologies of firms in the foldable display sector analyzing patent co-classification Network. Results show that the number of patent applications has rapidly increased since 2014, and 92% of these patents are held by two panel manufacturers, SDC and LGD, and two device manufacturers, SEC and LGE. Network analysis shows that the two panel manufacturers' core technologies are similar and two device manufacturers are notably different. This research provides implications to the sector. Moreover, this study provides unique results drawn from co-classification network analysis, and therefore, our research suggests patent co-classification analysis as an effective tool for technology planning.

• Journal of Korean Society for Quality Management
• /
• v.50 no.1
• /
• pp.21-33
• /
• 2022

Purpose: As most defense technologies are classified as confidential, the corresponding International Patent Classifications (IPCs) require special attention. Consequently, the list of defense-related IPCs has been managed by the government. This paper aims to evaluate the defense-related IPCs and propose a methodology to revalidate and improve the IPC classification scheme. Methods: The patents in military technology and their corresponding IPCs during 2009~2020 were utilized in this paper. Prior to the analysis, patents are divided into private and public sectors. Social network analysis was used to analyze the convergence structure and central defense technology, and association rule mining analysis was used to analyze the convergence pattern. Results: While the public sector was highly cohesive, the private sector was characterized by easy convergence between technologies. In addition, narrow convergence was observed in the public sector, and wide convergence was observed in the private sector. As a result of analyzing the core technologies of defense technology, defense-related IPC candidates were identified. Conclusion: This paper presents a comprehensive perspective on the structure of convergence of defense technology and the pattern of convergence. It is also significant because it proposed a method for revising defense-related IPCs. The results of this study are expected to be used as guidelines for preparing amendments to the government's defense-related IPC.