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Forecasting Vacant Technology of Patent Analysis System using Self Organizing Map and Matrix Analysis

자기조직화 지도와 매트릭스분석을 이용한 특허분석시스템의 공백기술 예측

  • 전성해 (청주대학교 바이오정보통계학과) ;
  • 박상성 (고려대학교 정보경영공학부) ;
  • 신영근 (고려대학교 정보경영공학부) ;
  • 장동식 (고려대학교 정보경영공학부) ;
  • 정호석 (인포베이스)
  • Published : 2010.02.28

Abstract

Patent analysis is the extracting knowledge which is needed for the company's research and development strategy through accumulated worldwide patent database. In order to set the future direction of corresponding technology which is scheduled to be developed, the technology trends and deployment processes are identified by analyzing results of present patent applications. The patent analysis provides the required results for analyzing present patent applications. In this paper, we will carry out technology classification for related patent analysis methods and systems. Moreover we will investigate and analyze related domestic patents, U.S. patents and IEEE papers. Due to the characteristics of technology sector, not only patents are applied but also research papers are released actively about patent analysis system. We will analyze patents according to the technology classification by using the final searching results which come from the selected search words in this study. To find necessary niche technology which is needed for patent analysis system, matrix analysis was performed to all of valid patents and papers. Identifying the technology development trends of registered patent analysis systems, and presenting the future direction of technology development which is related to patent analysis system. To figure out the technology which is developed relatively weak based on domestic patents, U.S patent and research papers by analyzing the valid patents and papers with statistical test and self-organizing map quantitatively. Then, presenting the necessity of this technology development.

Keywords

Patent Data;Patent Analysis System;Matrix Analysis;Statistical Test;SOM

References

  1. 제대식, 이은철, 윤국섭, 지식경영과 특허전략, 세종서적, 2000.
  2. 이종옥, 이규현, 정선양, 조성복, 윤진효, R&D 관리, 경문사, 2005.
  3. 박용태, 차세대 기술혁신을 위한 기술지식 경영, 생능출판사, 1998.
  4. 박용태, 공학도와 경영마인드, 생능출판사, 2007.
  5. 하정출, 지식경영론, 도서출판 두남, 2005.
  6. 특허청 정보기획팀, 한국발명진흥회 정보활용지원팀, 특허와 정보분석(개정판), 성민, 2007.
  7. K. Kasravi and M. Risov, “Patent Mining - Discover y of Business Value from Patent Repositories,” Proceedings of 40th Annual Hawaii International Conference on System Sciences, pp.54–54, 2007.
  8. M. Fattori, G. Pedrazzi, and R. Turra, “Text mining applied to patent mapping: a practical business case,” World Patent Information Vol.25, pp.335-342, 2003. https://doi.org/10.1016/S0172-2190(03)00113-3
  9. Y. Liang, R and Tan, J. Ma, “Patent analysis with text mining for TRIZ,” Proceedings of International Conference on Management of Innovation and Technology, pp.1147-1151, 2008.
  10. G. Nizar, K. Khaled, and D. Rose, “Supporting Patent Mining by using Ontology-based Semantic Annotations,” Proceedings of International Conference on Web Intelligence, pp.435-438, 2007.
  11. A. J. C. Trappey, S. C. I. Lin, and A. C. L. Wang, “Using neural network categorization method to develop an innovative knowledge management technology for patent document classification,” Proceedings of International Conference on Computer Supported Cooperative Work in Design, Vol.2, pp.830-835, 2005.
  12. A. J. C. Trappey, C. V. Trappey, and B. H. S. Kao, “Automated Patent Document Summarization for R&D Intellectual Property Management,” Proceedings of International Conference on Computer Supported Cooperative Work in Design, pp.1-6, 2006.
  13. M. W. Brinn, J. M. Fleming, F. M. Hannaka, C. B. Thomas, and P. A. Beling, “Investigation of forward citation count as a patent analysis method,” Proceedings of Systems and Information Engineering Design Symposium, pp.1-6, 2003.
  14. Y. Lai, H. Che and S. Wang, “Managing Patent Legal Value via Fuzzy Neural Network Incorporated with Factor Analysis Based on Patent Infringement Lawsuits,” Proceedings of International Conference on Wireless Communications, Networking and Mobile Computing, pp.1-6, 2008.
  15. B. Yoon and S. Lee, “Patent analysis for technology forecasting: Sector-specific applications,” Proceedings of IEEE International Conference on Engineering Management, pp.1-5, 2008.
  16. L. Sun and Y. Song, “Research on clustered patent mapping visualization and interaction,” Proceedings of 9th International Conference on Computer-Aided Industrial Design and Conceptual Design, pp.1130-1133, 2008.
  17. C. Wu, Y. Ken and T. Huang, “The Support Vector Machine Classification System for Patent Document Information Importance Analysis,” Proceedings of International Conference on BioMedical Engineering and Informatics, pp.375-379, 2008.
  18. J. Zhang, H. Zhang, J. Sun, and R. Tan, “Technique of product technology evolutionary potential mapping based on patent analysis,” Proceedings of International Conference on Industrial Engineering and Engineering Management, pp.2033-2037, 2007.
  19. Y. Iino, Y. Yamada, and S. Hirokawa, “Structural Analysis of R & D Division from Patent Documents,” Proceedings of International Conference on e-Business Engineering, pp.423-428, 2008.
  20. C. Kim, H. Lee, and Y. Park, “A Taxonomical Classification of Business Models on Mobile Business: Patent Analysis and SOM Mapping,” Proceeding of IEEE International Conference on Management of Innovation and Technology, Vol.1, pp.478-482, 2006. https://doi.org/10.1109/ICMIT.2006.262209
  21. K. V. Indukuri, P. Mirajkar, and A. Sureka, “An Algorithm for Classifying Articles and Patent Documents Using Link Structure,” Proceedings of International Conference on Web-Age Information Management, pp.203-210, 2008.
  22. http://ieeexplore.ieee.org/search
  23. Y. Tseng, C. Lin, and Y. Lin, “Text mining techniques for patent analysis,” Information Processing & Management, Vol.43, pp.1216-1247, 2007. https://doi.org/10.1016/j.ipm.2006.11.011
  24. P. Losiewicz, D. W. Oard, and R. N. Kostoff, “Textual Data Mining to Support Science and Technology Management,” Journal of Intelligent Information Systems, Vol.15, pp.99-119, 2000. https://doi.org/10.1023/A:1008777222412
  25. http://www.kipris.or.kr

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