• Title/Summary/Keyword: 특허 통계분석

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Patent and Statistics, What's the Connection? (특허와 통계학, 그 연결은?)

  • Jun, Sung-Hae;Uhm, Dai-Ho
    • Communications for Statistical Applications and Methods
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    • v.17 no.2
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    • pp.205-222
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    • 2010
  • A patent is a right of intellectual properties to an inventor or its assignee for a limited period under an international law. Not only in an invention of new machines, but it is competitive for using and creating technology in the world based on the patents. Most of the business models are good examples for patented technology, however a statistical analyzing model could be another one. In this paper we study and analyze the patents for the statistical analyzing and data mining models which are currently applied and registered, and suggest a statistical tool for analyzing and categorizing patent data. For this study all the patents in Korea and U.S. are listed and searched to sample the only cases concerning statistics.

일본 특허정보 활용사례

  • Kim, Bong-Jin
    • Patent21
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    • s.46
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    • pp.16-17
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    • 2003
  • 일본에서도 특허통계를 가지고 다양한 분석을 수행하는 방법에 대한 소개가 많이 되어 있다. 특허통계를 이용한 분석이 점점 증가하는 이유는 특허출원이 어느 정도는 기업의 연구개발의 활성도를 반영하고 있기 때문이다. 이번에 소개할 특허출우너순위로 본 기업의 연구투자와 가격결정자란 보고서는 경제산업조사회의 특허뉴스(2001.8.16)와 토미타 교수의 홈페이지(http;//hal2000.itakura.to.yo.ac.jp/~t4tomita)에 연재되어있는 것으로 1995년부터 1998년까지 공개된 특허정보를 대상으로 개별특허의 가치평가를 배제하고 일본에 출원된 기업의 특허건수 순위를 통해 분석한 보고서이다.

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A Study on the Statistical Analysis of Korea Patent Information (한국특허정보의 통계분석에 관한 연구)

  • Uhm, Dai-Ho;Chang, Young-Bae;Jeong, Eui-Seop
    • Journal of Information Management
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    • v.41 no.3
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    • pp.27-44
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    • 2010
  • Most research about patent data analyzes the trend of technologies using a Patent Map(PM), and suggests the frequencies and trend of patents in a certain topic using tables or graphs in Excel. However, more advanced analysis tools are recently needed to compare the trends among national and international industries. This research discussed why statistical analysis is needed to improve the reliability in PM analysis, and the research compares the trends of patents in Korea between 1990 and 2004 by years, International Patent Classification(IPC) sections, and countries using the frequencies and Poisson regression model. The statistical analysis is also suggested and applied to R&D studies.

연구개발성과평가를위한 국내외 사례연구

  • Jang, Je-Yeon
    • Patent21
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    • s.67
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    • pp.2-13
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    • 2006
  • 과학기술활동에 의해 창출된 발명은 주로 특허에 의해 보호되고 있으나, 특허통계ㆍ지표에 대해서 국제적인 기준이 마련되지 않아 국제비교가 어려운 실정이며, 측정요소들의 조합에 의해 특허통계ㆍ지표의 종류 또한 매우 다양하지만, 이 지표를 모두가 과학기술활동을 측정하는 데에 유용한지에 대해서는 의문시된다. 따라서 그 대안으로서 각국 국가연구개발사업의 성과평가지표 활용사례 및 활용되고 있는 특허통계ㆍ지표를 중심으로 분석ㆍ연구하고자 한다.

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Current Patent Status of Pet Food in Korea (펫푸드(반려동물 식품)분야 국내 특허 동향 분석)

  • Lee Yun Ju;Song Joon Seok
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.5
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    • pp.625-633
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    • 2023
  • The global pet culture-related industry is currently experiencing a trend of expansion. Within the pet industry, pet food holds a significant share, occupying a substantial portion. Presently, the domestic pet food market exhibits a high dependency on imported products, underscoring the critical importance of prioritizing the acquisition of intellectual property rights to ensure competitiveness and facilitate technological development within the relevant industry. we have undertaken an assessment of the current status and prospects of domestic pet food patents. Specifically, we have conducted temporal and applicant-specific statistical analyses, as well as IPC technology analyses, to examine the stages of technological advancement, corporate technological development and innovation capabilities, patent application distribution, and the technological landscape of key enterprises and research institutions. The research findings indicate that domestic research activities related to pet food have entered a mature phase, and the trends in patent applications for domestic pet food indicate a notable participation of multinational corporations alongside domestic enterprises.

Analysis of Artificial Intelligence's Technology Innovation and Diffusion Pattern: Focusing on USPTO Patent Data (인공지능의 기술 혁신 및 확산 패턴 분석: USPTO 특허 데이터를 중심으로)

  • Baek, Seoin;Lee, Hyunjin;Kim, Heetae
    • The Journal of the Korea Contents Association
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    • v.20 no.4
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    • pp.86-98
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    • 2020
  • The artificial intelligence (AI) is a technology that will lead the future connective and intelligent era by combining with almost all industries in manufacturing and service industry. Although Korea is one of the world's leading artificial intelligence group with the United States, Japan, and Germany, but its competitiveness in terms of artificial intelligence patent is relatively low compared to others. Therefore, it is necessary to carry out quantitative analysis of artificial intelligence patents in various aspects in order to examine national competitiveness, major industries and future development directions in artificial intelligence technology. In this study, we use the IPC technology classification code to estimate the overall life cycle and the speed of development of the artificial intelligence technology. We collected patents related to artificial intelligence from 2008 to 2018, and analyze patent trends through one-dimensional statistical analysis, two-dimensional statistical analysis and network analysis. We expect that the technological trends of the artificial intelligence industry discovered from this study will be exploited to the strategies of the artificial intelligence technology and the policy making of the government.

Patent citation network analysis (특허 인용 네트워크 분석)

  • Lee, Minjung;Kim, Yongdai;Jang, Woncheol
    • The Korean Journal of Applied Statistics
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    • v.29 no.4
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    • pp.613-625
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    • 2016
  • The development of technology has changed the world drastically. Patent data analysis helps to understand modern technology trends and predict prospective future technology. In this paper, we analyze the patent citation network using the USPTO data between 1985 and 2012 to identify technology trends. We use network centrality measures that include a PageRank algorithm to find core technologies and identify groups of technology with similar properties with statistical network models.

Performance Comparison of Statistics-Based Machine Learning Model for Classification of Technical Documents (기술문서 분류를 위한 통계기반 기계학습 모델 성능비교 및 한계 연구)

  • Kim, Jin-gu;Yu, Heonchang
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.05a
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    • pp.393-396
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    • 2022
  • 본 연구는 국방과학기술 분야의 특허 및 논문 실적을 이용하여 통계기반 기계학습 모델 4 종을 학습하고, 실제 분석 대상기관의 데이터 입력결과를 분석하여 실용성에 대한 한계점 분석을 목적으로 한다. 기존 연구에서는 특허분류코드를 기준으로 분류하여 특수 목적으로 활용하거나 세부 연구 범위 내 연구 주제탐색 및 특징연구 등 미시적인 관점에서의 상세연구 활용 목적인 반면, 본 연구는 거시적인 관점에서 연구의 전체적인 흐름과 경향성 파악을 목적으로 한다. 이에 ICT 기술 138 종의 특허 및 논문 30,965 건과 국방과학기술 192 종의 특허 및 논문 23,406 건을 학습데이터로 각 모델을 학습하였다. 비교한 통계기반 학습모델은 Support Vector Machines, Decision Tree, Naive Bayes, XGBoost 모델이다. 학습데이터에 대한 학습검증 단계에서는 최대 99.4%의 성능을 보였다. 다만, 실제 분석대상기관의 특허 및 논문 12,824 건으로 입력분석한 결과, 모델별 편향성 문제, 데이터 전처리 이슈, 다중클래스 및 다중레이블 문제를 확인, 도출한 문제에 대한 해결방안을 제시하고 추가 연구의 방향성을 제시한다.