• Title/Summary/Keyword: Korea Patent Data

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Big Data Smoothing and Outlier Removal for Patent Big Data Analysis

  • Choi, JunHyeog;Jun, Sunghae
    • 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.

An Empirical Analysis about the Effect on Performance of Firm's Patent Competency : Focusing on the High Performance Venture Firms in Korea (기업의 특허 역량이 성과에 미치는 영향에 관한 실증 분석 : 우수 벤처기업을 중심으로)

  • Ahn, Yeon S.
    • Knowledge Management Research
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    • v.11 no.1
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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.

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A Novel Classification Model for Efficient Patent Information Research (효율적인 특허정보 조사를 위한 분류 모형)

  • Kim, Youngho;Park, Sangsung;Jang, Dongsik
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.15 no.4
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    • pp.103-110
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    • 2019
  • A patent contains detailed information of the developed technology and is published to the public. Thus, patents can be used to overcome the limitations of traditional technology trend research and prediction techniques. Recently, due to the advantages of patented analytical methodology, IP R&D is carried out worldwide. The patent is big data and has a huge amount, various domains, and structured and unstructured data characteristics. For this reason, there are many difficulties in collecting and researching patent information. Patent research generally writes the Search formula to collect patent documents from DB. The collected patent documents contain some noise patents that are irrelevant to the purpose of analysis, so they are removed. However, eliminating noise patents is a manual task of reading and classifying technology, which is time consuming and expensive. In this study, we propose a model that automatically classifies The Noise patent for efficient patent information research. The proposed method performs Patent Embedding using Word2Vec and generates Noise seed label. In addition, noise patent classification is performed using the Random forest. The experimental data is published and registered with the USPTO among the patents related to Ocean Surveillance & Tracking Network technology. As a result of experimenting with the proposed model, it showed 73% accuracy with the label actually given by experts.

Competitiveness Analysis for Artificial Intelligence Technology through Patent Analysis (특허분석을 통한 인공지능 기술 분야 경쟁력 분석: 특허 시장성과 기술력 질적 분석을 중심으로)

  • Kwak, Hyun;Lee, Seongwon
    • The Journal of Information Systems
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    • v.28 no.3
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    • pp.141-158
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    • 2019
  • Purpose Artificial Intelligence (AI) is a core technology, leading the 4th industrial revolution. This study aims to diagnose the Korean's national competitiveness for AI technologies through patent analyses. Design/methodology/approach In this study, KIWEE and Derwent Innovation databases were used as data source of patents. we extracted 10,510 AI patents data with keywords and classified them into 15 subcategories of AI technology. We executed patent analyses for activity index, patent intensity index, technology strength, and patent family size and diagnosed Korea's national competitiveness in AI industry. Findings The results showed that Korea is less competitive than the United States and Japan in AI industry. However, patent amount has increased since 2010, which is encouraging result. This study has implication on the need for human and R&D investment in AI industry.

LED Knowledge Map through Competition Analysis based on Intellectual Property (지식재산권 기반 경쟁력 분석을 통한 LED 지식 맵)

  • Koo, Young-Duk;Kwon, Young-Il;Jeong, Dae-Hyun
    • The Journal of the Korea institute of electronic communication sciences
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    • v.8 no.1
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    • pp.7-12
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    • 2013
  • In this paper, we provide a basic data to constitute knowledge map through analysis of competition situation such as analysis of patent activity for each nationality, analysis of patent activity for each applicant for a patent, analysis of patent activity for each technical area and analysis of competition status for power of security for market which consider qualitative level. In order to analysis LED data, we choose patent data of LED.

LED Knowledge Map through a Patent Application (특허 출원 분석을 통한 LED 지식 맵)

  • Koo, Young-Duk;Jeong, Dae-Hyun;Kwon, Young-Il
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.5
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    • pp.961-966
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    • 2012
  • In this paper, we analyze a main patent positioning to analyze data based on patent application as stage of data collection to organize knowledge map of LED through patent application. We also analyze the present condition of patent application for technology sector. We propose basic data to make knowledge map through the analysis of technical distribution for applicant by each country.

Patome: Database of Patented Bio-sequences

  • Kim, SeonKyu;Lee, ByungWook
    • Genomics & Informatics
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    • v.3 no.3
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    • pp.94-97
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    • 2005
  • We have built a database server called Patome which contains the annotation information for patented bio-sequences from the Korean Intellectual Property Office (KIPO). The aims of the Patome are to annotate Korean patent bio-sequences and to provide information on patent relationship of public database entries. The patent sequences were annotated with Reference Sequence (RefSeq) or NCBI's nr database. The raw patent data and the annotated data were stored in the database. Annotation information can be used to determine whether a particular RefSeq ID or NCBI's nr ID is related to Korean patent. Patome infrastructure consists of three components­the database itself, a sequence data loader, and an online database query interface. The database can be queried using submission number, organism, title, applicant name, or accession number. Patome can be accessed at http://www.patome.net. The information will be updated every two months.

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.

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

  • Koo, Ki-Kwan;Lee, Deok-Ki;Hong, Jong-Chul;Park, Soo-Uk
    • New & Renewable Energy
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    • v.8 no.3
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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.

A Study on Efficient Noise Filtering of Patent Data Analysis and Level Assessment of Patent Technology which improve reliability (특허 데이터 분석시 효율적인 노이즈 제거와 신뢰도가 향상된 특허 기술수준 평가에 관한 연구)

  • Kang, Hee-Seop;Lee, Seung-Ho
    • Journal of Korea Technology Innovation Society
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    • v.15 no.1
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    • pp.105-128
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    • 2012
  • This paper proposes the technological level assessment which improved reliability and the efficient noise elimination methods in the process of establishing patent map analysis data. In order to eliminate efficiently noise (removed by the manual process in the past), the paper applies the Logical Operator 'AND', makes it a program in excel VBA(Visual Basic Application), and obtains the valid data. For the improved reliability technological level assessment of the patents, the study calculates average number of claims, Patent Family Size(PFS), Cites Per Patent (CPP), Triad Patent Families, Standardization Patent Diversification Index (stdPCPI), and haF-index(Hirsch a Family index). The result which applied noise exclusion work showed less than 10% of acquired patent data ratio and confirmed high reliability. The result that apply proposed technological level assessment index makes sure that balanced technological level assessment which improved reliability by producing synthetic technological level assessment.

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