• 한국전자통신학회논문지
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• 제7권5호
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• pp.955-960
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• 2012

본 논문에서는 LED의 지식 맵 구성을 위한 초기 준비단계로서 지식 재산권을 기반으로 경쟁력을 분석하여 관련 분야의 지식 맵 구성에 기초자료로 활용할 수 있는 방법을 제시한다. 분석 데이터 추출을 위해 분석 대상 기술을 LED를 선정하고 특허 데이터를 중심으로 최근 특허 비율, 특허 활동 지수, 시장 확보 지수, 인용도 지수를 추출하고 특허 수준 분석을 통하여 LED 응용 분야 종합 분석 결과를 제시하였다.

• 신재생에너지
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• 제8권3호
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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.

• 경영과학
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• 제24권2호
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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.

• 한국지능시스템학회논문지
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• 제25권5호
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• pp.470-476
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• 2015

빅 데이터는 여러 분야에서 다양하게 사용되고 있다. 예를 들어, 컴퓨터학과 사회학에서 빅 데이터에 대한 서로간의 접근방법에 대한 차이는 있겠지만 빅 데이터의 분석을 통한 활용 측면에서는 공통적인 부분을 갖는다. 따라서 대부분의 분야에서 빅 데이터에 대한 의미 있는 분석과 활용은 필요하게 된다. 통계학과 기계학습은 빅 데이터의 분석을 위한 다양한 방법론을 제공한다. 본 논문에서는 빅 데이터분석 과정에 대하여 알아보고 수집된 빅데이터의 원천에서부터 분석을 거쳐 최종적으로 분석결과를 활용하는 전체 과정을 위한 효율적인 빅 데이터 분석방법에 대하여 연구한다. 특히, 빅 데이터의 특성을 갖는 여러 데이터 중 하나인 특허문서 데이터에 대하여 빅데이터분석을 적용하여 효과적인 특허분석을 수행하고 이 결과를 연구개발 기획에 적용하는 방법론에 대하여 제안한다. 제안방법에 대한 실제적용을 위하여 전 세계 특허데이터베이스로부터 실제 기업의 전체 출원, 등록 특허 문서를 수집, 분석하고 연구개발 업무에 활용하는 전 과정에 대한 사례연구를 수행하였다.

• 산업경영시스템학회지
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• 제46권4호
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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.

• 한국컴퓨터정보학회논문지
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• 제24권1호
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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.

• 한국전자통신학회논문지
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• 제7권5호
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• pp.961-966
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• 2012

본 논문에서는 LED의 지식 맵 구성을 위한 자료 수집 단계로서 특허 출원을 기반으로 데이터를 분석을 위해 국가별 출원 현황, 출원인별 출원 현황을 통하여 주요 특허 포지셔닝을 분석한다. 또한 기술 분야별 특허 출원 현황과 분석하며 출원인 국적별 기술 분포 분석을 통하여 지식 맵 작성을 위한 기본 자료를 제시한다.

• 지식경영연구
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• 제11권1호
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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.

• 한국지능시스템학회논문지
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• 제23권5호
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• pp.406-411
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• 2013

빅 데이터는 여러 분야에서 다양한 개념으로 사용된다. 예를 들어, 컴퓨터학과 사회학에서 빅 데이터에 대한 접근방법에 차이가 있지만, 데이터분석 관점에서는 공통적인 부분을 갖는다. 즉, 공학이든 사회과학이든 빅 데이터에 대한 분석은 반드시 필요하다. 통계학과 기계학습은 빅 데이터의 분석을 위한 대표적인 분석도구이다. 본 논문에서는 빅 데이터분석을 위한 학습도구에 대하여 알아보고 검색된 빅 데이터 원천에서부터 분석을 거쳐 최종적으로 분석결과를 사용하는 전체과정에 대하여 효율적인 빅 데이터학습 절차에 대하여 제안한다. 특히, 대표적인 빅 데이터 구조를 갖고 있는 특허문서에 대하여 빅데이터학습을 적용하여 특허분석을 수행하고 이 결과를 기술예측에 적용하는 방법에 대하여 연구한다. 제안방법에 대한 실제적용을 위하여 전 세계 특허청으로부터 빅 데이터 관련 특허문서를 검색하여 텍스트 마이닝의 전처리와 통계학의 다중선형회귀분석을 이용한 구체적인 빅 데이터학습에 대한 사례연구를 수행하였다.

• 지식경영연구
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• 제11권1호
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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.