• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.961-966
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• 2012

In this paper, we analyze a main patent positioning to analyze data based on patent application as stage of data collection to organize knowledge map of LED through patent application. We also analyze the present condition of patent application for technology sector. We propose basic data to make knowledge map through the analysis of technical distribution for applicant by each country.

• The Journal of Information Systems
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• v.28 no.3
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• pp.141-158
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• 2019

Purpose Artificial Intelligence (AI) is a core technology, leading the 4th industrial revolution. This study aims to diagnose the Korean's national competitiveness for AI technologies through patent analyses. Design/methodology/approach In this study, KIWEE and Derwent Innovation databases were used as data source of patents. we extracted 10,510 AI patents data with keywords and classified them into 15 subcategories of AI technology. We executed patent analyses for activity index, patent intensity index, technology strength, and patent family size and diagnosed Korea's national competitiveness in AI industry. Findings The results showed that Korea is less competitive than the United States and Japan in AI industry. However, patent amount has increased since 2010, which is encouraging result. This study has implication on the need for human and R&D investment in AI industry.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.143-149
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• 2022

Since patent documents contain detailed results of research and development technologies, many studies on various patent analysis methods for effective technology analysis have been conducted. In particular, research on quantitative patent analysis by statistics and machine learning algorithms has been actively conducted recently. The most used patent data in quantitative patent analysis is technology keywords. Most of the existing methods for analyzing the keyword data were models based on the Gaussian probability distribution with random variable on real space from negative infinity to positive infinity. In this paper, we propose a model using gamma probability distribution to analyze the frequency data of patent keywords that can theoretically have values from zero to positive infinity. In addition, in order to determine the regression equation of the gamma-based regression model, two-mode network is constructed to visualize the technological association between keywords. Practical patent data is collected and analyzed for performance evaluation between the proposed method and the existing Gaussian-based analysis models.

• Journal of Distribution Science
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• v.18 no.6
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• pp.77-82
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• 2020

Purpose: In the period of international integration, how is the implementation of intellectual property regulation in developing countries? Do intellectual property rights help attract more Foreign direct investment (FDI)? This study aims to show the effect of intellectual property rights, reflect in the number of patent registered (Patent distribution into two components: Patent_residents and Patent_non-residents) on FDI attraction in Vietnam. Research design, data and methodology: Using Autoregressive distributed lag (ARDL) model for the data collected from 1990 to 2018 with EViews version 9 software. Conclusions: The results indicate that the number of patent protection has a positive effect on FDI in both short term and long term. In particular, only patent registration of foreign individuals and organizations has a significant positive effect on attracting FDI, while that of Vietnamese patents is not statistically significant. From the results of this study, we provide some recommendations to help attract FDI based on raising awareness of intellectual property rights: Increase international cooperation for innovation to learn and encourage patent; Improve the capac ity of inventing as well as the ability to register patents of Vietnamese people; Government agencies are tasked to support a nd review registration procedures; Encouraging patent registration based on the patent.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.406-411
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• 2013

Big data issue has been considered in diverse fields. Also, big data learning has been required in all areas such as engineering and social science. Statistics and machine learning algorithms are representative tools for big data learning. In this paper, we study learning tools for big data and propose an efficient methodology for big data learning via legacy data to practical application. We apply our big data learning to patent analysis, because patent is one of big data. Also, we use patent analysis result for technology forecasting. To illustrate how the proposed methodology could be applied in real domain, we will retrieve patents related to big data from patent databases in the world. Using searched patent data, we perform a case study by text mining preprocessing and multiple linear regression of statistics.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.257-261
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• 1997

Patents often serve as leading indicators of technological change. This patenting activity reflected R&D (Research & Development) of new technology. The purpose of this study is to set up a forecasting model that anticipate the number of domestic patent applications and the number of patents granted relating to R&D inputs (R&D expenditure, R&D manpower) at the level of three industrial sectors in Korea : electrical-electronic, machinery, chemical etc. In this study, forecasting models were used trend extrapolation and a set of regressions. Both Theil's inequality coefficient and MAE(Mean Absolute Error) were utilized to test the precision of predicted value. The patent data and the R&D data were based on Indicators of Industrial Technology data throught 1980 to 1996. The major results obtained in this study are as follows (1) The regression model is more useful for forecasting the trends of the number of patent applications and patents granted than the trend extrapolation method. (2) The variance of Theil's inequality is smaller in patent applications than in patent granted.

• Genomics & Informatics
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• v.3 no.3
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• pp.94-97
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• 2005

We have built a database server called Patome which contains the annotation information for patented bio-sequences from the Korean Intellectual Property Office (KIPO). The aims of the Patome are to annotate Korean patent bio-sequences and to provide information on patent relationship of public database entries. The patent sequences were annotated with Reference Sequence (RefSeq) or NCBI's nr database. The raw patent data and the annotated data were stored in the database. Annotation information can be used to determine whether a particular RefSeq ID or NCBI's nr ID is related to Korean patent. Patome infrastructure consists of three components­the database itself, a sequence data loader, and an online database query interface. The database can be queried using submission number, organism, title, applicant name, or accession number. Patome can be accessed at http://www.patome.net. The information will be updated every two months.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.4
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• pp.41-49
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• 2019

Patents are system to promote the development of industry by disclosing technology. The importance of recent patent is being emphasized. For this reason, companies apply for many patents. And they analyze the patent. Patent analysis helps to protect and foster their technology. Previously this method has been carried out by experts. Expert-based patent analysis, however, has the disadvantage of being time-consuming and expensive. Consequently, we try to solve this problems by developing prediction model. Therefore, this paper proposes a data-based patent analysis method using quantitative indicator and textual information. We confirmed the practical applicability of the proposed method through 1,831 autonomous vehicle patents. As a result, it was possible to confirmed that safety and lane detection related technologies are important.

• Journal of the Korea Convergence Society
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• v.9 no.2
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• pp.251-257
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• 2018

As the use of big data is necessary for increasing business value, the size of the big data market is getting bigger. Accordingly, it is important to apply competitive patents in order to gain the big data market. In this study, we conducted the patent analysis based keyword network to analyze the trend of big data patents. The analysis procedure consists of big data collection and preprocessing, network construction, and network analysis. The results of the study are as follows. Most of big data patents are related to data processing and analysis, and the keywords with high degree centrality and between centrality are "analysis", "process", "information", "data", "prediction", "server", "service", and "construction". we expect that the results of this study will offer useful information in applying big data patent.

• Journal of Information Technology Applications and Management
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• v.27 no.1
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• pp.125-145
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• 2020

We explore technology ecosystem of smart surgical medical system by analyzing patent data applied for in Korea and Japan. First, a review of trends of patent application by country/technological domain show that there exist a minority of technology domains focused on R&D, which represent their trends have been increasingly active. Also, while a number of Japanese firms mainly consist of the patent market of Japan, in case of the Korean market, a few universities, SMEs, and foreign firms are found to be the main applicants. As a result of the network analysis with the links as the relations of co-patenting, the relationships, which are active of convergence and knowledge spillover among the heterogeneous technology domains within each market, as well as the technology domains, which are the most active in international cooperation among each homogeneous domain, could get derived and visualized in the ecosystem. In addition, the technology domains in each patent market with leading locations, roles, and influence in the network can also be identified through the centrality analysis. In this study, the analysis for technology competitiveness are carried out focusing on patent activity and patent impact. The results denote that across all domains, the Japanese market may possess higher patent activity and patent impact compared to the Korean market. In consequence, we derive the position map for comparison by country and technology domain from a perspective considering comprehensively the multi-dimensional attributes based on the results of both network analysis and technology competitiveness.