Earticle

초록

영어

Emerging technology drives technological development and innovation in diverse fields of technology. Emerging technology forecasting can predict the possible areas of emerging technology. However, it is difficult to forecast the emerging technology because most technology forecasting tasks depend on the subjective experience of experts. Patent analysis is an objective method to recognize the trends in technological development. Many patent analysis methods have been researched; these methods apply text mining techniques to analyze the text data of patent documents such as the title and abstract. This approach has some limitations, namely the computing cost and information loss associated with the preprocessing step of text mining. Therefore, we propose a new patent information analysis to overcome these problems. Using the International Patent Classification codes from the patent documents of a target technology, we construct an emerging technology forecasting model. This research combines statistical inference and neural networks to construct our model for new patent information analysis. We perform a case study to verify how our research can be practically applied, using nanotechnology as the target technology. Therefore, we contribute this research to R&D planning.

목차

Abstract
 1. Introduction
 2. Emerging Technology Forecasting
 3. New Patent Information Analysis for Emerging Technology Forecasting
 4. Experimental Results
 5. Conclusions
 References

키워드

저자

• Sunghae Jun [ Department of Statistics, Cheongju University, Chungbuk, Korea ] Corresponding Author
• Seung-Joo Lee [ Department of Statistics, Cheongju University, Chungbuk, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Software Engineering and Its Applications

• 간기

  월간

• pISSN

  1738-9984

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605