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  • 标题:Patent Analysis Using Bayesian Network Models
  • 本地全文:下载
  • 作者:Sunghae Jun ; Seung-Joo Lee
  • 期刊名称:International Journal of Software Engineering and Its Applications
  • 印刷版ISSN:1738-9984
  • 出版年度:2013
  • 卷号:7
  • 期号:3
  • 出版社:SERSC
  • 摘要: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.
  • 关键词:Bayesian network model; patent analysis; probability distribution; technology;management; technological association
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