Journal of the Korea Convergence Society (한국융합학회논문지)

Korea Convergence Society (한국융합학회)
권호 표지
DOI QR코드

DOI QR Code

Big Data Patent Analysis Using Social Network Analysis

키워드 네트워크 분석을 이용한 빅데이터 특허 분석

  • Received : 2017.12.13
  • Accepted : 2018.02.20
  • Published : 2018.02.28
Download PDF
⟨ Previous Next ⟩

Abstract

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.

빅데이터의 활용은 비즈니스 가치를 높이는데 필수요소가 됨에 따라 빅데이터 시장의 규모가 점점 더 커지고 있다. 이에 따라 빅데이터 시장을 선점하기 위해서는 경쟁력 있는 특허를 선점하는 것이 중요하다. 본 연구에서는 빅데이터 특허의 동향을 분석하기 위하여 영문 키워드 네트워크 기반 특허분석을 수행하였다. 분석 절차는 빅데이터 수집 및 전처리, 네트워크 구성, 네트워크 분석으로 구성되어 있다. 연구 결과는 다음과 같다. 빅데이터 특허 대다수는 예측 등을 위한 데이터 처리를 위한 특허이며, analysis, process, information, data, prediction, server, service, construction 키워드가 연결정도 중심성 및 매개 중심성이 높았다. 본 연구의 분석결과는 향후 빅데이터 특허 출원 시 참고할 수 있는 유용한 정보로 활용될 수 있다.

Keywords

References

  1. IDC. (2017). Data Age 2025: The Evolution of Data to Life-Critica.
  2. S. M. Rho. (2014). Big data analysis platform technology R&D trend through patent analysis. Journal of Digital Convergence, 12(9). 169-175. https://doi.org/10.14400/JDC.2014.12.9.169
  3. B. Y. Lee. J. T. Lim & J. S. Yoo (2013). Utilization of social media analysis using big data. Journal of the Korea Contents Association, 13(2), 211-219. https://doi.org/10.5392/JKCA.2013.13.02.211
  4. J. S. Kim. (2014). Big data analysis technologies and practical examples. Journal of the Korea Contents Association, 12(1), 14-20.
  5. IDC. (2016). Worldwide semiannual big data and analytics spending guide, https://www.idc.com.
  6. K. B. Kim & H. J. Cho (2017). A Study on the Regulation Improvement Measures for Activation of Internet of Things and Big Data Convergence. Journal of the Korea Convergence Society, 8(5), 29-35. https://doi.org/10.15207/JKCS.2017.8.5.029
  7. S. H. Lee & D. W. Lee. (2013). Current status of big data utilization. Journal of Digital Convergence, 11(2), 229-233. https://doi.org/10.14400/JDPM.2013.11.12.229
  8. J. S. Kim. (2012). Big data utilization and related technique and technology analysis. Journal of the Korea Contents Association, 10(1), 34-40.
  9. J. H. Choi. H. S. Kim & N. G. Im. (2011). Keyword network analysis for technology forecasting. Journal of Intelligence and Information Systems, 17(4), 227-240.
  10. Korean Intellectual Property Office, http://www.kipo.go.kr.
  11. S. U. Bae. D. G. Kwag. & E. Y. Park. (2017). The Study of the Aviation Industrial Technology Convergence through Patent analysis. Journal of the Korea Convergence Society, 6(5), 119-225.
  12. S. H. Jun. (2011). Technology forecasting of intelligent systems using patent analysis. Journal of Korean Institute of Intelligent Systems, 21(2), 100-105. https://doi.org/10.5391/JKIIS.2011.21.1.100
  13. D. M. Kim. Y. J. Choi. & C. W. Lee. (2011). Analysis the mobile user-interface in patent. Journal of the Korea Contents Association, 11(12), 455-465. https://doi.org/10.5392/JKCA.2011.11.12.455
  14. T. K. Kim. H. R. Choi. & H. C. Lee. (2016). A study on the research trends in fin tech using topic modeling. Journal of the Korea Academia-Industrial Cooperation Society, 17(11), .670-681. https://doi.org/10.5762/KAIS.2016.17.11.670
  15. Y. H. Kim (2003). Social network analysis. Seoul : Pakyoungsa.
  16. Y. H. Kim. (2003). Social network theory. Seoul : Pakyoungsa.
  17. D. W. Son. (2002). Social network analysis. Seoul : Kyungmoonsa.
  18. I. Y. Choi. Y. S. Lee. & J. K. Kim. (2010). A usage pattern analysis of the academic database using social network analysis in K university library. Journal of the Korean Society for Information Management, 27(1), 25-40. https://doi.org/10.3743/KOSIM.2010.27.1.025
  19. J. K. Kim. I. Y. Choi. H. K. Kim. & N. H. Kim (2009). Social network analysis to analyze the purchase behavior of churning customers and loyal customers. Korean Management Science Review, 26(1), 183-196.
  20. C. S. Park. (2012). A Study on the network structure of the public administration academic community using the coauthor network from 1998 to 2009. Korean Society and Public Administration, 22(4), 129-153.
  21. J. C. Kho. K. T. Cho. & Y. H. Cho. (2013). A study on recent research trend in management of technology using keywords network Analysis. Journal of Intelligence and Information Systems, 19(2), 101-123. https://doi.org/10.13088/jiis.2013.19.2.101
  22. J. Y. Lee. & P. S. Jang. (2017). Study on Research Trends in Airline Industry using Keyword Network Analysis: Focused on the Journal Articles in Scopus, Journal of the Korea Convergence Society, 8(5), 169-178. https://doi.org/10.15207/JKCS.2017.8.5.169
  23. I. Y. Choi. B. J. An. & S. H. Jung. (2015). Analysis of co-authorship network in the Korean journal of dance studies. Korean Journal of Sports Science, 24(3), 1263-1271.