Journal of Korean Society of Industrial and Systems Engineering (산업경영시스템학회지)

Society of Korea Industrial and System Engineering (한국산업경영시스템학회)
권호 표지
DOI QR코드

DOI QR Code

Nano Technology Trend Analysis Using Google Trend and Data Mining Method for Nano-Informatics

나노 인포매틱스 기반 구축을 위한 구글 트렌드와 데이터 마이닝 기법을 활용한 나노 기술 트렌드 분석

  • Received : 2017.09.18
  • Accepted : 2017.12.15
  • Published : 2017.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

Our research is aimed at predicting recent trend and leading technology for the future and providing optimal Nano technology trend information by analyzing Nano technology trend. Under recent global market situation, Users' needs and the technology to meet these needs are changing in real time. At this point, Nano technology also needs measures to reduce cost and enhance efficiency in order not to fall behind the times. Therefore, research like trend analysis which uses search data to satisfy both aspects is required. This research consists of four steps. We collect data and select keywords in step 1, detect trends based on frequency and create visualization in step 2, and perform analysis using data mining in step 3. This research can be used to look for changes of trend from three perspectives. This research conducted analysis on changes of trend in terms of major classification, Nano technology of 30's, and key words which consist of relevant Nano technology. Second, it is possible to provide real-time information. Trend analysis using search data can provide information depending on the continuously changing market situation due to the real-time information which search data includes. Third, through comparative analysis it is possible to establish a useful corporate policy and strategy by apprehending the trend of the United States which has relatively advanced Nano technology. Therefore, trend analysis using search data like this research can suggest proper direction of policy which respond to market change in a real time, can be used as reference material, and can help reduce cost.

Keywords

References

  1. Daly, E.M. and Haahr, M., Social network analysis for routing in disconnected delay-tolerant MANETs, ACM, 2007, Vol. 9, No. 14, pp. 32-40.
  2. Fraley, C.A. and Raftery, E., How Many Clusters? Which Clustering Method? Answers Via Model-Based Cluster Analysis, The Computer Journal, 1998, Vol. 41, No. 8, pp. 578-588. https://doi.org/10.1093/comjnl/41.8.578
  3. Fritsch, M. and Monz, M.K., The impact of network structure on knowledge transfer : an application of social network analysis in the context of regional innovation networks, Ann Reg Sci., 2010, Vol. 44, pp. 21-38. https://doi.org/10.1007/s00168-008-0245-8
  4. Han, J.Y., NA, J.G., and Kim, C.B., Network Analysis of Technology Convergence on Decentralized Energy by Using Patent Information : Focused on Daegu City Area, J. Soc. Korea Ind. Syst. Eng., 2016, Vol. 39, No. 3, pp. 156-169. https://doi.org/10.11627/jkise.2016.39.3.156
  5. Kim, M.J., Kang, S.G., and Bae, S.H., Green Growth and Nanotechnology Policy-Focus on France, Germany, and Northern Europe-, National Nanotechnology Policy Center, 2015, pp. 1-44.
  6. Lee, J.K., Kim, Y.O., and Kang, N.E., Analysis of Climate Change Researches Related to Water Resources in the Korean Peninsula, Climate Change Research, 2012, Vol. 3, No. 1, pp. 71-88.
  7. Lee, J.W., Lee, S.D., and Kim, Y.S., Supply and demand technology manpower in the field of nanotechnology, Dasan institute of economic research, 2013, (http://www.dier.or.kr/?c=common&m=download &orgName=6ae3472c47bf98fd7e5454dd52e54af2.pdf&viewName=%EB%82%98%EB%85%B8%EA%B8%B0%EC%88%A0%EB%B6%84%EC%95%BC_%EA%B8%B0%EC%88%A0%EC%9D%B8%EB%A0%A5_%EC%88%98%EA%B8%89%EC%A0%84%EB%A7%9D.pdf&mcd=m0301 (accessed Aug., 16, 2017))
  8. Lee, S., Heo, Y.G., and Kim, H.M., Traffic planning using Big Data : Midnight bus and accident reduction, Seoul Transportation Policy Package, 2017, pp. 1-16.
  9. Lee, S.E., Jeong, E.H., and Park, M.H., Analysis of energy new industry trend using Big Data, Innovation Studies, 2016, Vol. 11, pp. 1-22.
  10. Min, K.M., Kim, H.T., and Ji, Y.G., A Pilot Study on Applying Text Mining Tools to Analyzing Steel Industry Trends : A Case Study of the Steel Industry for the Company "P", The Journal of Society for e-Business Studies, 2014, Vol. 19, No. 3, pp. 51-64. https://doi.org/10.7838/jsebs.2014.19.3.051
  11. Oh, Y.J. and Chung, G.E., Comparison of R&D investment between Korea and major countries, KISTEP, 2015, pp. 1-14.
  12. WIRED.com, Data is The New Oil of the Digital Economy, WIRED, 2014, https://www.wired.com/insights/2014/07/data-new-oil-digital-economy(accessed Aug., 16, 2017).
  13. Yu, S.H., Market trends of nanotechnology and nanomaterials, KISTI, 2016, pp. 1-7.

Cited by

  1. 구글 트렌드 빅데이터를 통한 바이오의약품의 시장 점유율 분석과 추정 vol.43, pp.2, 2020, https://doi.org/10.11627/jkise.2020.43.2.014
  2. SNS 빅데이터 및 검색포털 트렌드와 마약류 사건 통계간의 비교 및 의미분석 연구 vol.19, pp.2, 2021, https://doi.org/10.14400/jdc.2021.19.2.231
  3. 텍스트 마이닝과 의미 네트워크 분석을 활용한 뉴스 의제 분석: 코로나 19 관련 감정을 중심으로 vol.27, pp.1, 2017, https://doi.org/10.13088/jiis.2021.27.1.047