• 제목/요약/키워드: patent data

검색결과 573건 처리시간 0.024초

키워드 네트워크 분석을 이용한 빅데이터 특허 분석 (Big Data Patent Analysis Using Social Network Analysis)

  • 최주철
    • 한국융합학회논문지
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    • 제9권2호
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    • pp.251-257
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    • 2018
  • 빅데이터의 활용은 비즈니스 가치를 높이는데 필수요소가 됨에 따라 빅데이터 시장의 규모가 점점 더 커지고 있다. 이에 따라 빅데이터 시장을 선점하기 위해서는 경쟁력 있는 특허를 선점하는 것이 중요하다. 본 연구에서는 빅데이터 특허의 동향을 분석하기 위하여 영문 키워드 네트워크 기반 특허분석을 수행하였다. 분석 절차는 빅데이터 수집 및 전처리, 네트워크 구성, 네트워크 분석으로 구성되어 있다. 연구 결과는 다음과 같다. 빅데이터 특허 대다수는 예측 등을 위한 데이터 처리를 위한 특허이며, analysis, process, information, data, prediction, server, service, construction 키워드가 연결정도 중심성 및 매개 중심성이 높았다. 본 연구의 분석결과는 향후 빅데이터 특허 출원 시 참고할 수 있는 유용한 정보로 활용될 수 있다.

빅데이터 분석 도구 R을 활용한 효율적인 특허 검색에 관한 연구 (A study on the efficient patent search process using big data analysis tool R)

  • 장청윤;장정환;김석주;이현근;이창호
    • 대한안전경영과학회지
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    • 제15권4호
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    • pp.289-294
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    • 2013
  • Due to sudden transition to intellectual society corresponding with fast technology progress, companies and nations need to focus on development and guarantee of intellectual property. The possession of intellectual property has been the important factor of competition power. In this paper we developed the efficient patent search process with big data analysis tool R. This patent search process consists of 5 steps. We result that at first this process obtain the core patent search key words and search the target patents through search formula using the combination of above patent search key words.

기업의 특허활동이 경영성과에 미치는 영향에 관한 연구 - 통신 산업의 시차분석을 중심으로 (A Study on the Effect of Firm's Patent Activity on Business Performance - Focuss on Time Lag Analysis of IT Industry)

  • 이준혁;김갑조;박상성;장동식
    • 디지털산업정보학회논문지
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    • 제9권2호
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    • pp.121-137
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    • 2013
  • Now days, firm's technology capability is recognized as important factor to forecast and to evaluate firm's business performance. There are many efforts to develop useful indicators by applying patent information that includes concrete description about technology. Many previous studies analyzed relationship between patent indicators and firm's performance. But they didn't consider time gap between a point of firm's invention activity and a point of firm's performance improvement. They didn't considered a character of industrial fields either. To overcome these limitations, we selected IT industry for target analysis industry. Time-series patent data and financial data from 41 American IT firms between 2000 and 2011 were used to analyze. In this study, We empirically analyzed subsequent effect of patent indicators on firm's business performance by using correlation analysis and regression analysis.

국내외 신재생에너지 기술 경쟁력 분석 - 태양광·연료전지를 중심으로 - (An Analysis of the Competitiveness of Renewable Energy Technologies)

  • 구기관;이덕기;홍종철;박수억
    • 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.

Comparative analysis of US and China artificial intelligence patents trends

  • Kim, Daejung;Jeong, Joong-Hyeon;Ryu, Hokyoung;Kim, Jieun
    • 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.

통계적 텍스트 마이닝을 이용한 빅 데이터 전처리 (A Big Data Preprocessing using Statistical Text Mining)

  • 전성해
    • 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.

LED 지식 맵 구성을 위한 지식재산권 기반 기술 경쟁력 분석 (Analysis of a Technical Competition based on Intellectual Property for Constitute of LED Knowledge Map)

  • 구영덕;권영일;정대현
    • 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.

토픽 모형과 ChatGPT를 활용한 스마트팩토리 연관 특허 빅데이터 분석에 관한 연구 (A Study on Big Data Analysis of Related Patents in Smart Factories Using Topic Models and ChatGPT)

  • 김상국;윤민영;권태훈;임정선
    • 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.

고효율 전기기기 특허동향 분석 (Patent map development of High-efficiency electric machineries)

  • 박종진;이창호;김남정
    • 한국기술혁신학회:학술대회논문집
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    • 한국기술혁신학회 2000년도 추계 학술대회(The 2000 Autumn Conference of korea Technology Inovation Society)(한국기술혁신학회)
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    • pp.177-193
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    • 2000
  • In foreign countries, high-efficiency electric machineries have been developed in view of cost reduction, environmental issues, energy conservation etc. Especially they focus on developing energy conservation measures and demand-side management. Thus, patent application and secure of patent claims are on the rise as important issues in this field. In this paper, we analyzed patent application trends about inverters, ac/dc converters, reactive power control equipments, high-efficiency transformers and electric ballasts among high-efficiency electric machineries. First, we analyzed general technology trends, and constructed patent technology data. Second, we graphed patent application trends in terms of application years, assignees and nations.

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특허 데이터 및 재무 데이터를 활용한 글로벌 기업의 인공지능 하드웨어 연구개발 효율성 분석 (Analysis of Research and Development Efficiency of Artificial Intelligence Hardware of Global Companies using Patent Data and Financial data)

  • 박지민;이봉규
    • 한국멀티미디어학회논문지
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    • 제23권2호
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    • pp.317-327
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    • 2020
  • R&D(Research and Development) efficiency analysis is a very important issue in academia and industry. Although many studies have been conducted to analyze R&D(Research and Development) efficiency since the past, studies that analyzed R&D(Research and Development) efficiency considering both patentability and patent quality efficiency according to the financial performance of a company do not seem to have been actively conducted. In this study, measuring the patent application and patent quality efficiency according to financial performance, patent quality efficiency according to patent application were applied to corporate groups related to artificial intelligence hardware technology defined as GPU(Graphics Processing Unit), FPGA(Field Programmable Gate Array), ASIC(Application Specific Integrated Circuit) and Neuromorphic. We analyze the efficiency empirically and use Data Envelopment Analysis as a measure of efficiency. This study examines which companies group has high R&D(Research and Development) efficiency about artificial intelligence hardware technology.