专利可视化
专利分析
构造(python库)
数据科学
计算机科学
技术预测
推论
新兴技术
预处理器
数据预处理
信息技术
数据挖掘
知识管理
人工智能
操作系统
程序设计语言
作者
Sunghae Jun,Seung-Joo Lee
出处
期刊:International Journal of Software Engineering and its Applications
[Global Vision Press]
日期:2012-07-01
卷期号:6 (3): 107-116
被引量:10
摘要
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.
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