Time Series Analysis of Patent Keywords for Forecasting Emerging Technology


KIPS Transactions on Software and Data Engineering, Vol. 3, No. 9, pp. 355-360, Sep. 2014
10.3745/KTSDE.2014.3.9.355,   PDF Download:

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.


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Cite this article
[IEEE Style]
J. C. Kim, J. H. Lee, G. J. Kim, S. S. Park, D. S. Jang, "Time Series Analysis of Patent Keywords for Forecasting Emerging Technology," KIPS Transactions on Software and Data Engineering, vol. 3, no. 9, pp. 355-360, 2014. DOI: 10.3745/KTSDE.2014.3.9.355.

[ACM Style]
Jong Chan Kim, Joon Hyuck Lee, Gab Jo Kim, Sang Sung Park, and Dong Sick Jang. 2014. Time Series Analysis of Patent Keywords for Forecasting Emerging Technology. KIPS Transactions on Software and Data Engineering, 3, 9, (2014), 355-360. DOI: 10.3745/KTSDE.2014.3.9.355.