• Title/Summary/Keyword: patent information analysis

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Monitoring Trends of Safety Technology Development of Industry Fields Using Patent Analysis (특허분석을 활용한 산업별 안전기술개발 동향 모니터링)

  • Choi, Yuri;Suh, Yongyoon
    • Journal of the Korean Society of Safety
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    • v.35 no.4
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    • pp.92-100
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    • 2020
  • Along with the rapid development of industrial technology, the industrial structure has been continuously changed. Accordingly, safety technologies have been gradually developed to be applied into various industrial fields as well, not limited to a specific industry area. As a result, it became important to analyze and predict trends of safety technology development in order to establish technology strategies for industrial safety. In particular, since patents are easily accessible to gather the technology and business information, many studies have highlighted technology forecasting using patent information. Thus, this study proposes the patent analysis of monitoring trends of safety technologies of industry fields, taking into account both static and dynamic aspects through index and text analysis. First, patent documents containing safety-related keywords are collected from the WIPSON database for extracting technology information. Then, the development trends of safety technologies by industry fields are identified and analyzed through the analysis of indicators such as marketability, growth, and activation. The results of various indicator analyses of safety technologies are visualized to compare among industrial safety technologies for businesses and technology developers. Second, textmining algorithm is applied to identify trends of specific technology keywords of major industries extracted from patent index analysis. As a result, it is expected that the safety manager uses the patent analysis of safety technologies to provide safety technology information with safety-related companies and institutes. The extracted safety technologies are applicable to business practice and predict future promising technologies.

A Study on prediction of patent big data using supervised learning with dimension reduction model (지도학습 기반의 차원축소 모델을 이용한 특허 빅데이터 예측에 관한 연구)

  • Lee, Juhyun;Lee, Junseok;Kang, Jiho;Park, Sangsung;Jang, Dongsik;Hong, Sungwook;Kim, Sunyoung
    • 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.

Analysis of Zeolite Membrane Using Patent Information (특허정보에 의한 제올라이트 분리막 연구동향 고찰)

  • Im, Eun-Jung;Kim, Sung-Hyun;Kim, Sang-Gon;Hyeon, Dong-Hun;Park, Sun-Hee
    • Clean Technology
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    • v.18 no.3
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    • pp.307-311
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    • 2012
  • Patents is a strong asset. Samsung and Apple's patent lawsuit is a prime example. So many countries reinforce the intellectual property and they lay the emphasis on the patent. Utilizing the patent information efficiently is basic to the patent analysis. Patent information will provide for new science and technology information sources, international code is classified according to the international patent system IPC, being easily accessible. In this paper, analysis of foreign and domestic patents for zeolite technologies analysis using IPC. The current of technology development in such countries as Korea, USA, Japan, China and EU was analyzed by classifying the patents for 1992 through 2011 according to registration country, assignee, calendar year and technology area.

A Study on the Prediction for the OCR Technology Development Trajectory based on the Patent and Article Information (특허와 논문정보를 활용한 OCR 기술발전 동향예측에 관한 연구)

  • Won Jun, Kim;Sang Kon, Lee;Sung Kuk, Pyo
    • Journal of Information Technology Services
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    • v.21 no.6
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    • pp.39-51
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    • 2022
  • As the 4th Industrial Revolution emerged as a key to improving national competitiveness, OCR technology, one of the major technologies in the 4th industry is in the spotlight. Since characters in various images contain a lot of information, OCR technology for recognizing these characters has evolved into technology used in many industries. In this paper, trends in OCR technology were identified and predicted using thesis data published in 'RISS' and patent data by International patent classification (IPC) under the theme of Optical character recognition (OCR). For patent data 20,000 patents related to OCR technology from 2002 to 2020 were used as data, and 432 papers from 2012 to 2022 were used as data. Through time-series analysis, each patent data and thesis data were investigated since when OCR technology has developed, and various keyword analysis predicted which technology will be used in the future. Finally, the direction of future OCR technology development was presented through network association analysis with patent data and thesis data.

Exploring Convergence Fields of Safety Technology Using ARM-Based Patent Co-Classification Analysis (공통특허분류 분석을 활용한 안전기술융합분야 탐색 : Association Rule Mining(ARM) 접근법)

  • Suh, Yongyoon
    • Journal of the Korean Society of Safety
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    • v.32 no.5
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    • pp.88-95
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    • 2017
  • As the safety fields are expanding to a variety of industrial fields, safety technology has been developed by convergence between industrial safety fields such as mechanics, ergonomics, electronics, chemistry, construction, and information science. As the technology convergence is facilitating recently advanced safety technology, it is important to explore the trends of safety technology for understanding which industrial technologies have been integrated thus far. For studying the trends of technology, the patent is considered one of the useful sources that has provided the ample information of new technology. The patent has been also used to identify the patterns of technology convergence through various quantitative methods. In this respect, this study aims to identify the convergence patterns and fields of safety technology using association rule mining(ARM)-based patent co-classification(co-class) analysis. The patent co-class data is especially useful for constructing convergence network between technological fields. Through linkages between technological fields, the core and hub classes of convergence network are explored to provide insight into the fields of safety technology. As the representative method for analyzing patent co-class network, the ARM is used to find the likelihood of co-occurrence of patent classes and the ARM network is presented to visualize the convergence network of safety technology. As a result, we find three major convergence fields of safety technology: working safety, medical safety, and vehicle safety.

Preliminary Study of Bioinformatics Patents and Their Classifications Registered in the KIPRIS Database

  • Park, Hyun-Seok
    • Genomics & Informatics
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    • v.10 no.4
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    • pp.271-274
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    • 2012
  • Whereas a vast amount of new information on bioinformatics is made available to the public through patents, only a small set of patents are cited in academic papers. A detailed analysis of registered bioinformatics patents, using the existing patent search system, can provide valuable information links between science and technology. However, it is extremely difficult to select keywords to capture bioinformatics patents, reflecting the convergence of several underlying technologies. No single word or even several words are sufficient to identify such patents. The analysis of patent subclasses can provide valuable information. In this paper, I did a preliminary study of the current status of bioinformatics patents and their International Patent Classification (IPC) groups registered in the Korea Intellectual Property Rights Information Service (KIPRIS) database.

Analysis of BIM Technology Structure and Core Technology Using Patent Co-classification Network Analysis (특허 동시분류 네트워크 분석을 활용한 BIM 기술구조와 핵심기술 분석)

  • Park, Yoo-Na;Lee, Hye-Jin;Lee, Seok-Hyoung;Choi, Hee-Seok
    • Journal of KIBIM
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    • v.10 no.2
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    • pp.1-11
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    • 2020
  • BIM(Building Information Modeling) is a salient technology for influential innovation in the construction industry. The patent network analysis is useful for suggesting the direction of technology development and exploring the research and development field. Therefore, the purpose of this study is to analyze the BIM technology structure and core technologies according to the convergence of BIM technology and market expansion. In this study, social network analysis was conducted by establishing a co-classification IPC network for the United States BIM patent. In particular, the characteristics of the major technical areas in the BIM technology network were identified through centrality analysis. G06F017/00, digital computing or data processing method, is a core technology field in the BIM network. Arrangements, apparatus or systems for transmission of digital information, H04L029/00 is an influential technology across the network. B25J009/00 for program controlled manipulators is an intermediary technology field and G06T019/00, manipulating 3D models or images for computer graphics, is an important field for technological development competitiveness.

Patent Keyword Analysis using Gamma Regression Model and Visualization

  • Jun, Sunghae
    • 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.

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

  • Choi, Ju-Choel
    • 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.

A Study on Analysis of Pilates-related Patent Information (필라테스 분야 특허 정보 분석에 관한 연구)

  • Chi, Dong-Cheol;Kim, Jong-Hyuck
    • Journal of the Korea Convergence Society
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    • v.13 no.4
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    • pp.513-519
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    • 2022
  • The 4th industrial revolution has made our life convenient, and the development of new technologies has brought affluent life. Considering that the 4th industrial revolution is a next-generation industrial revolution led by robot technology, life science, and artificial intelligence, the need for convergence research in sports field stimulated the continuous efforts for the academic foundation of sports. Recently, as interest in home training has increased due to the COVID-19 pandemic, the Pilates has also attracted much attentions demand for related supplies has increased. This is an demonstration that COVID-19 has had an impact on the sports industry ecosystem. The purpose of this study was, accordingly, to identify current trends through accurate patent information related to Pilates and to provide basic data for future studies on sports convergence industry and sports intellectual property. For the purpose, based on the data from Jan. 1 to Dec. 31, 2021 provided by KIPRIS (www.kipris.or.kr), the patent information search service provided by the Korean Intellectual Property Office, patent status analysis, international patent classification (IPC) patent analysis, and detailed patent analysis by classification were performed.