Earticle

초록

영어

Technology management is important to both companies and nations. Recently, economic competitiveness for both depends on technological prowess. Patents are a representative index of technological competitiveness because a patent document has diverse and detailed information about developed technologies. Hence, patent analysis is an efficient tool for technology management activities such as R&D planning and technology marketing. In this paper, we propose a patent analysis method using Bayesian network models. A Bayesian network is a graphical model representing the relationships between variables. We use International Patent Classification codes as the variables of a Bayesian network model to obtain the technological associations between codes. We verify the performance of our research using retrieved patent documents related to the BMW motor company.

목차

Abstract
 1. Introduction
 2. Bayesian Network Models
 3. Patent Analysis Using Bayesian Network Models
 4. Experimental Result
 5. Conclusion
 References

키워드

저자

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

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