• Journal of Korea Society of Industrial Information Systems
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• v.23 no.2
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• pp.63-73
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• 2018

Academia and research institutes mainly use qualitative methods that rely on expert judgments to understand and predict research trends and science and technology trends. Since such a technique has the disadvantage of requiring much time and money, in this study, science and technology trends were predicted using keyword network analysis. To that end, 13,618 AI (Artificial Intelligence) patent abstracts were analyzed using keyword network analysis in three separate lots based on the period of the submission of each abstract: analysis period 1 (January 1, 2002 - December 31, 2006), analysis period 2 (January 1, 2007 - December 31, 2011), and analysis period 3 (January 1, 2012 - December 31, 2016). According to the results of frequency analyses, keywords related to methods in the field of AI application appeared more frequently as time passed from analysis period 1 to analysis period 3. In keyword network analyses, the connectivity between keywords related to methods in the field of AI application and other keywords increased over time. In addition, when the connected keywords that showed increasing or decreasing trends during the entire analysis period were analyzed, it could be seen that the connectivity to methods and management in the field of AI application was strengthened while the connectivity to the field of basic science and technology was weakened. According to analysis of keyword connection centrality, the centrality value of the field of AI application increased over time. According to analysis of keyword mediation centrality during analysis period 3, keywords related to methodologies in the field of AI application showed the highest mediation value. Therefore, it is expected that methods in the field of AI application will play the role of powerful intermediaries in AI hereafter. The technique presented in this paper can be employed in the excavation of tasks related to regional innovation or in fields such as social issue visualization.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.37-46
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• 2016

Patent application as achievements from R&D institutions in public sector have quantitatively increased by expanding R&D investment for enhancing competitiveness but there have been few tangible outputs from the investment. From this reason, TLO(Technology Transfer&Licensing Organization) and its operation becomes more important to implement technology transfer and commercialization and to bring success in the related business. To get work done more efficiently and to improve utilizing products of the R&D in the TLO, this research is to draw domains and activities of TLO and establish its task systems by prioritizing activities. From literature reviews and expert interviews, we generated 6 work domains and 21 task items. Applying AHP analysis, we discriminated the relative importance from task items and analyzed its priority. The finding of this research can provide implications for TLO to increase work efficiency and improve its performance.

• Journal of Korea Technology Innovation Society
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• v.15 no.2
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• pp.443-460
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• 2012

Technology is closely related to industrial development and various studies have been performed to understand the linked structure for knowledge flow between the technology and industry. The research, however, wasn't carried out to flow for Korea National Research and Development projects. In this study, linked structure for technology-industry was discussed by utilizing patent data performed in actual National R&D using NTIS Information of the national research and development, and then it was analyzed how knowledge flows between the technology and industry are flowing. It should be defined that the individual applications expected by researchers at the start of the research and technology-industry applications actually applied from the research performances after research was completed. As a result, it was confirmed in most projects the flow of knowledge was occurring to predicted industries before the start of the R&D. However, the technology was applied to unexpected industry in three industries such as Y09(medical, precision and optical instruments), Y10(electrical and mechanical equipment), Y11(automotive and transportation equipment). The results of this study will be able to contribute to planning for efficient investment strategy of technology-industry by investigating the technology-industry knowledge flow relations of national R&D projects.

• Journal of Korea Technology Innovation Society
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• v.14 no.1
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• pp.1-21
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• 2011

Technical change and technological innovation have become major drivers of economic progress in the knowledge oriented economies where growth, productivity, and competitiveness are increasingly based on improved technologies, novel products, upgraded processes or customized services. The creation of new knowledge, modifying or improving existent knowledge, or imitation of others, has become central to economic development. New discoveries, state-of-the-art information gathering procedures, or successful problem solving routines are often at he core of these innovations. Despite the generally acknowledged importance of science in many high-tech areas of major economic relevance, there is few science-related statistics to be found in high-profile international benchmarking reports. This paper aims to provide an answer by advancing our understanding of the possibilities of indicators quantifying linkages between science and technology. Central are the concepts of innovation capability and science/technology interface, which are used to assemble a wide range of empirical studies and quantitative indicators to summarize their possibilities and limitations for producing comparative statistics. For the purpose of the study, we extracted the US patents by Korean assignees or inventors, scientific papers cited in the patents in order to analyze the characteristics of linkage of scientific knowledge flows. The review focuses on indicators dealing with flows of written or codified information, and indicators of inventiveness that capture the non-codifiable tacit knowledge dimension. General conclusions will be drawn with a view towards further developments in the foreseeable future, suggesting new avenues for the design and implementation of patent-based and inventor-based relationships between scientific research and technical development within the context of regional or national systems of innovation.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.87-107
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• 2016

Understanding market convergence has became essential for small and mid-size enterprises. Identifying convergence items among heterogeneous markets could lead to product innovation and successful market introduction. Previous researches have two limitations. First, traditional researches focusing on patent databases are suitable for detecting technology convergence, however, they have failed to recognize market demands. Second, most researches concentrate on identifying the relationship between existing products or technology. This study presents a platform to identify the opportunity of market convergence by using product databases from a global B2B marketplace. We also attempt to identify convergence opportunity in different industries by applying Structural Hole theory. This paper shows the mechanisms for market convergence: attributes extraction of products and services using text mining and association analysis among attributes, and network analysis based on structural hole. In order to discover market demand, we analyzed 240,002 e-catalog from January 2013 to July 2016.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1161-1170
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• 2014

In global competition like today, intellectual property of novel areas such as traditional knowledge, traditional creation, hereditary resource, etc. are perceived as important resources. Therefore making solid competitive power in overall knowledge resources like cultural contents, brand, design etc. in nation is a pressing question. Accordingly in this study, to prepare for intellectual property rights dispute and advantage-sharing problem that would be variously derived from the Nagoya Protocol which will come into force after 2014, this research selected 200 knowledge of middle region in Korea from 2,047 literal and 931 oral knowledge using preconditioning process. The order of priority of top 50 of them was ranked by a quantitative research method, the Delphi survey. Among them, 30 was literal traditional knowledge and 20 was oral traditional knowledge. Result of this research could be used later as basic material for qualitative researches like the focus group interviewing. Furthermore in this paper is meaningful; the selected traditional knowledge can contribute remarkably to traditional biologic knowledge resource in nation which can be acknowledged in international society, announcing validity (hold precedence for patent) later on.

• Management & Information Systems Review
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• v.38 no.3
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• pp.55-80
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• 2019

Recently, many companies improving their management performance by building a powerful brand value which is recognized for trademark rights. However, as growing up the size of online commerce market, the infringement of trademark rights is increasing. According to various studies and reports, cases of foreign and domestic companies infringing on their trademark rights are increased. As the manpower and the cost required for the protection of trademark are enormous, small and medium enterprises(SMEs) could not conduct preliminary investigations to protect their trademark rights. Besides, due to the trademark image search service does not exist, many domestic companies have a problem that investigating huge amounts of trademarks manually when conducting preliminary investigations to protect their rights of trademark. Therefore, we develop an intelligent similar trademark search model to reduce the manpower and cost for preliminary investigation. To measure the performance of the model which is developed in this study, test data selected by intellectual property experts was used, and the performance of ResNet V1 101 was the highest. The significance of this study is as follows. The experimental results empirically demonstrate that the image classification algorithm shows high performance not only object recognition but also image retrieval. Since the model that developed in this study was learned through actual trademark image data, it is expected that it can be applied in the real industrial environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.949-955
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• 2020

In this Study, Social Network Analysis of IoT related patents in South Korea, China, and Japan was conducted from the viewpoint of patent informatics. To this end, 2,526 patents filed by PCT until December 2019 were investigated up to the subclass level of the IPC code. As a result, in the case of South Korea, representative IPC codes are in the order of G06Q, H04L, G06F, H04W, and the highest frequency of interconnection is H04L→H04W, H04W→H04L, H04W→H04B. In China, the representative IPC codes are in the order of H04L, H04W, G05B, G06Q. South Korea has strong technological convergence centered on the G06Q, while China has strong convergence centered around H04L and H04W. Moreover, in China, H04L and H04W have more diverse combinations than in South Korea in Section A, B, G, and H. In the future, it is necessary to study the diversity of technology convergence of H04L and H04W in China.

• The Journal of Society for e-Business Studies
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• v.26 no.1
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• pp.1-28
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• 2021

FinTech has been discussed as an important business area towards technology-driven financial innovation. The term fintech is a combination of finance and technology, which means ICT technology currently associated with all finance areas. The popularity of the fintech industry has significantly increased over time, with full investment and support for numerous startups. Therefore, both academia and practice tried to analyze the trend of the fintech area. Despite the fact, however, previous research has limitations in terms of collecting relevant databases for fintech and identifying proper application areas. In response, this study proposed a new method for analyzing the trend of Fintech fields by expanding Fintech's terminology and using network analysis and topic modeling. A new Fintech terminology list was created and a total of 18,341 patents were collected from USPTO for 10 years. The co-classification analysis and network analysis was conducted to identify the technological trends of patent classification. In addition, topic modeling was conducted to identify the trends of fintech in order to analyze the contents of fintech. This study is expected to help both managers and investors who want to be involved in technology-driven financial services seize new FinTech technology opportunities.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.5
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• pp.308-314
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• 2022

This study deals with the technology Convergence Analysis by IPC Code-Based Social Network Analysis of Healthcare Patents filed in Korea. The relationship between core technologies is visualized using Social Network Analysis. At the subclass level of healthcare patents, 1,155 cases (49.4%) of patents with complex IPC codes were investigated, and as a result of Social Network Analysis on them, the IPC codes with the highest Degree Centrality were A61B, G16H, and G06Q, in that order. The IPC codes with the highest Betweenness Centrality are in the order of A61B, G16H, and G06Q. In addition, it was confirmed that healthcare patents consist of two large technology clusters. Cluster-1 corresponds to related business models centered on A61B, G16H and G06Q, and Cluster-2 is consisting of H04L, H04W and H04B. The technology convergence core pairs of the healthcare patent is [G16H-A61B] and [G16H-G06Q] in Cluster-1, and [H04L-H04W] in Cluster-2. The results of this study can contribute to the development of core technologies for healthcare patents.