• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.955-960
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• 2012

In this paper, we analysis a competition to organize knowledge map as initial prepare stage based on intellectual property. We also propose the method that can be used to constitute knowledge map related in area to use basic data. In order to extract analysis data, we choose LED as an analysis technology. We provide the result of total analysis for LED application area through analysis of patent level after we extract recent patent ratio, activity index, patent family size, cites per patent as center of patent data.

• New & Renewable Energy
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• v.8 no.3
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• pp.30-37
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• 2012

In this study, we studied solar cell and fuel cell. To estimate the technology competitiveness, we used patent analysis using patent information and delphi method. For patent analysis, PII indicating the impact of patent was used. Also to analysis PII, citations data of registered and published patent were used from 2001 through 2010 in the United States, Japan, South Korea and the European Patent Office. And the delphi method results of the 'International trend analysis on the Green Energy Technology and the establishment of international cooperation models(2009)' were cited to estimate the technology level. According to the analysis results, Korea's patent registration growth rate was fairly high, but the patent impact and technology levels were significantly lower than in the United States, Japan and Germany. Especially in the solar cell, United States's PII is 1.8, but Korea's PII is 0.2. And the technology level of United States is 7 to 8, but Korea's is 5 to 6. Therefore, to improve technology competitiveness, Korea need to enhance the core technology R&D, and set up the consumer-oriented R&D strategy for commercialization from R&D planning phase. In this study, we analysed competitiveness of renewable energy which is not actively discussed. But there are limitations of the study because we used the result of past research and patent data in the past 10 years. Therefore to accurate research the period of patent data should be extended. Finally diverse indicators for measuring the technology competitiveness should be researched and developed.

• Korean Management Science Review
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• v.24 no.2
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• pp.1-18
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• 2007

This paper presents a consolidated patent index to measure national technology innovation and science technology activation, as well as index for the main constituent such as corporation, research organization by comprehensive analysis of existing patent index. It is classified by macroscopic index and analytical index in the consolidated patent index, in which macroscopic index is to present a degree of innovation in national scientific innovation and is divided into the Consolidated Patent Index and Index for comparison between countries. The analytical index basically designed to measure R&D activity by the main constituent is divided to present by quantitative index utilizing bibliographical data in patent and other technical publication related therein, and qualitative index for analysis of bibliographical data. In this paper, the Consolidated Patent Index is presented by adding Creation Index representing for patent by developing excellent technology, Evaluation Index representing valuable technology thereof, and Utility Index representing applicability diffused.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.470-476
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• 2015

Big data has been used in diverse areas. For example, in computer science and sociology, there is a difference in their issues to approach big data, but they have same usage to analyze big data and imply the analysis result. So the meaningful analysis and implication of big data are needed in most areas. Statistics and machine learning provide various methods for big data analysis. In this paper, we study a process for big data analysis, and propose an efficient methodology of entire process from collecting big data to implying the result of big data analysis. In addition, patent documents have the characteristics of big data, we propose an approach to apply big data analysis to patent data, and imply the result of patent big data to build R&D strategy. To illustrate how to use our proposed methodology for real problem, we perform a case study using applied and registered patent documents retrieved from the patent databases in the world.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.15-31
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• 2023

In this study, we propose a novel approach to analyze big data related to patents in the field of smart factories, utilizing the Latent Dirichlet Allocation (LDA) topic modeling method and the generative artificial intelligence technology, ChatGPT. Our method includes extracting valuable insights from a large data-set of associated patents using LDA to identify latent topics and their corresponding patent documents. Additionally, we validate the suitability of the topics generated using generative AI technology and review the results with domain experts. We also employ the powerful big data analysis tool, KNIME, to preprocess and visualize the patent data, facilitating a better understanding of the global patent landscape and enabling a comparative analysis with the domestic patent environment. In order to explore quantitative and qualitative comparative advantages at this juncture, we have selected six indicators for conducting a quantitative analysis. Consequently, our approach allows us to explore the distinctive characteristics and investment directions of individual countries in the context of research and development and commercialization, based on a global-scale patent analysis in the field of smart factories. We anticipate that our findings, based on the analysis of global patent data in the field of smart factories, will serve as vital guidance for determining individual countries' directions in research and development investment. Furthermore, we propose a novel utilization of GhatGPT as a tool for validating the suitability of selected topics for policy makers who must choose topics across various scientific and technological domains.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.25-32
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• 2019

With the rapid development of artificial intelligence technology, the patenting activities related to the fields of AI is increasing worldwide. In particular, a share of patent filed in China has exploded in recent years and overtakes the numbers in the US. In the present study, we focus our attention on the patenting activity of China and the US. We analyzed 6,281 and 13,664 patent applications in the US and China respectively between 2008 and 2018, and belonging to the "G06F(Electric Digital Data Processing)", "G06N(Computer Systems Based on Specific Computational Models)", "H04L(Transmission of Digital Information)" and nine more relevant technological classes, as indicated by the International Patent Classification(IPC). Our analysis contributes to: first, the understanding of patent application trends from foreign countries filed in the US and China, 2) patent application status by applicants category such as companies, universities and individuals, 3) the development direction and forecasting vacant technology of AI according to main IPC code. Through the analysis of this paper, we can suggest some implications for patent research related to artificial intelligence in Korea. Plus, by analyzing the most recent patent data, we can provide important information for future artificial intelligence technology research.

• 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.

• Knowledge Management Research
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• v.11 no.1
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• pp.83-96
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• 2010

In this study, the effect of firm's patent competency on the their management performance was analysed. The number of patents granted to Korean firms, patent grade score as of the firm's patent competence were considered in the perspectives of patent volume and patent value respectively. Specially the analysis were implemented focusing on the high performance venture ranked 200th in Korea. The patent source data were from the Korean Intellectual Property Office, Korean Credit Evaluation Information Company, and the Patent Evaluation System of KIPO and KIPA. And the year sales and net profit volume as of the firm's management performance data from the KIS. Management performance data are consisted of the mean sales, net profit and ROI during the 4 years from FY2005 to FY2008. Major results are as follows. The regression model were proved significantly that the year sales volume and net profit are effected by the number of patents and patent grade score. But the model including the ROI were shown not significantly. So it can be concluded that patent volume and patent value are the important factors on firm's financial performance as of the year sales volume and net profit. Also the regression model including the control variables, firm's number of employee and business year, the number of patents and patent grade score are the significant factors on firms performance. And regression coefficients of patent value model were higher than these of patent volume model. So it can be recognized that patent value of firms' patent competency are more important factor than the patent volume.

• 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.

• Knowledge Management Research
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• v.11 no.1
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• pp.65-81
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• 2010

This paper explores the determinants of the economic value of patents using a survival time analysis. The analysis is based on renewal information of about 250,000 patents filed from 1984 to 2005 in the Korea Intellectual Property Office. A patent right is valid only when its owner pays yearly maintenance fees. Failure to pay causes patent rights to be lapsed. We use the fact that more valued patents live longer and the lengths of their renewals can be closely related to their value. The value can be affected not only by its own technological aspects such as quality and breadth, but also by characteristics of its owners such as innovativeness and age. This paper presents patent-specific and firm-specific characteristics which influence patent value. The result of analysis implies that patent value depends on both the technological contents of the patent and general capabilities of a firm.