• Patent21
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• s.64
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• pp.4-10
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• 2005

본 보고서는 2005년 11월 3일 개최된 PATINEX(PATent INformation EXpo)에서 WIPO의 Mr.William Meredth가 발표한 자료인 "Trends in International Patent Statistics and Analysis"를 국문으로 재작성한 글입니다. <혁신기획팀 김민아 역>

• 한국신재생에너지학회:학술대회논문집
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• 2007.11a
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• pp.525-528
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• 2007

Geothermal Energy is related part of important the technology, and getting Patent statistics and analysis are targeted to Koran, Japan and America. Accoding to patent statistics, checking the analysis, developing speed of technology in korean and technology level and compared with America between Japan of technology. In this paper, Give help to national level can be achieved by reinforcing companies R&D, putting more concern and effort on getting straegical patents, activation of jog invention, expanding the quality Intellectual property(IP) & licensing Personnel, building a system responsive to international patent dispute. and national level can be archived by encouraging &supporting R&D of core technology, overseas applications of IP rights

• Patent21
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• s.65
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• pp.23-28
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• 2006

본 보고서는 2005년 11월 3일 개최된 PATINEX(PATent INformation EXpo)에서 USPTO의 Mr. Robert Johnson이 발표한 자료인 "Patent Statistics of the U.S.Patent and Trademark Office"를 국문으로 재작성한 글입니다. <혁신기획팀 김민아 역>

• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.77-84
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• 2016

In general statistical analysis, we need to make a normal assumption. If this assumption is not satisfied, we cannot expect a good result of statistical data analysis. Most of statistical methods processing the outlier and noise also need to the assumption. But the assumption is not satisfied in big data because of its large volume and heterogeneity. So we propose a methodology based on box-plot and data smoothing for controling outlier and noise in big data analysis. The proposed methodology is not dependent upon the normal assumption. In addition, we select patent documents as target domain of big data because patent big data analysis is a important issue in management of technology. We analyze patent documents using big data learning methods for technology analysis. The collected patent data from patent databases on the world are preprocessed and analyzed by text mining and statistics. But the most researches about patent big data analysis did not consider the outlier and noise problem. This problem decreases the accuracy of prediction and increases the variance of parameter estimation. In this paper, we check the existence of the outlier and noise in patent big data. To know whether the outlier is or not in the patent big data, we use box-plot and smoothing visualization. We use the patent documents related to three dimensional printing technology to illustrate how the proposed methodology can be used for finding the existence of noise in the searched patent big data.

• 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.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.719-728
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• 2016

In this paper, we analyzed IoT patent data using the social network analysis of keyword community network in patents related to Internet of Things technology. To identify the difference of IoT patent trends between Korea and USA, 100 Korea patents and 100 USA patents were collected, respectively. First, we first extracted important keywords from IoT patent abstracts using the TF-IDF weight and their correlation and then constructed the keyword network based on the selected keywords. Second, we constructed a keyword community network based on the keyword community and performed social network analysis. Our experimental results showed while Korea patents focus on the core technologies of IoT (such as security, semiconductors and image process areas), USA patents focus on the applications of IoT (such as the smart home, interactive media and telecommunications).

• 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.

• 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.

• 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.

• 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.