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http://dx.doi.org/10.3745/KTSDE.2014.3.9.355

Time Series Analysis of Patent Keywords for Forecasting Emerging Technology  

Kim, Jong-Chan (고려대학교 산업경영공학과)
Lee, Joon-Hyuck (고려대학교 산업경영공학과)
Kim, Gab-Jo (고려대학교 산업경영공학과)
Park, Sang-Sung (고려대학교 산업경영공학부)
Jang, Dong-Sick (고려대학교 산업경영공학부)
Publication Information
KIPS Transactions on Software and Data Engineering / v.3, no.9, 2014 , pp. 355-360 More about this Journal
Abstract
Forecasting of emerging technology plays important roles in business strategy and R&D investment. There are various ways for technology forecasting including patent analysis. Qualitative analysis methods through experts' evaluations and opinions have been mainly used for technology forecasting using patents. However qualitative methods do not assure objectivity of analysis results and requires high cost and long time. To make up for the weaknesses, we are able to analyze patent data quantitatively and statistically by using text mining technique. In this paper, we suggest a new method of technology forecasting using text mining and ARIMA analysis.
Keywords
Technology Forecasting; Text Mining; Patent Data; ARIMA Analysis;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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1 Korean Intellectual Property Office, Korean Invention Promotion Association, "Patent and information analysis (for researchers)," Kyungsung Books, pp.302-372, 2009.
2 J. D. Hamilton, Time series analysis, Princeton university press, pp.25-142, 1994.
3 B. U. Yoon and Y. T. Park, "A text mining based patent network: Analytical tool for high technology trend," Journal of High Technology Management Research, Vol.15, No.1, pp.37-50, 2004.   DOI   ScienceOn
4 R. Feldman and J. Sanger, The text mining hand book: advanced approaches in analyzing unstructured data, Cambridge university press, pp.1-13, 2007.
5 S. H. Jun, "An Efficient Text mining for Patent Information Analysis," Proceedings of KIIS Spring Conference, Vol.19, No.1, pp.255-257, 2009.
6 E. A. Elsayed and T. O. Boucher, Analysis and control of production systems, Prentice Hall, pp.7-61, 1993.
7 Y. H. Tseng, C.J. Lin, and Y. I. Lin, "Text mining technique for patent analysis," Information processing and management, Vol.43, No.5, pp.1216-1257, 2009.
8 S. H. Jun, "Technology forecasting of intelligent systems using patent analysis," Journal of Korean institute of intelligent systems, Vol.21, No.1, pp.100-105, 2011.   과학기술학회마을   DOI
9 Y. S. Kim, S. S Park, and D. S. Jang, "Patent data analysis using CLARA algorithm: OLED technology," Journal of Korea institute of information technology, Vol.10, No.6, pp.161-170, 2012.
10 B. U. Yoon and Y. T. Park, "A systematic approach for identifying technology opportunities: keywords-based morphology analysis," Technologycal forecasting and social change, Vol.72, No.2, pp.145-160, 2005.   DOI
11 S. J. Lee, B. U. Yoon, and Y. T. Park, "An approach to discovering new technology opportunities: keywords-based patent map approach," Technovation, Vol.29, No.6-7, pp. 481-497, 2009.   DOI   ScienceOn
12 V. S. Ediger and S. Akar, "ARIMA forecasting of primary energy demand by fuel in Turkey", Energy Policy, Vol.35, No.3, pp.1701-1708, 2007.   DOI
13 Wips on [internet], http://www.wipson.com/
14 KIPRIS [internet], http://www.kpris.or.kr/
15 J. C. Kim, J. H. Lee, G. J. Kim, S. S. Park, and D. S. Jang, "Time series analysis of patent keywords for forecasting emerging technology," The 2014 spring conference of the KIPS, Vol.21, No.1, pp.650-652, 2014.