[目的/意义]利用专利的动态特征识别技术转移潜力,可为高校和科研院所开展专利分级管理和运营工作提供支撑,促进专利技术的产业化。[方法/过程]专利特征在其生命周期呈现动态演变,本文基于动态专利引文网络,从动态发展的视角构建动态和静态相结合的专利技术转移潜力评价指标体系;以转让或许可专利的动态特征为学习对象,采用决策树方法建立技术转移预测模型,并进行实证模型检验。[结果/结论]专利在引文网络中的影响力对其转移转化潜力有较大的作用,实证检验基于决策树的转移预测模型具有较高的预测效果。通过监测专利动态特征,利用模型进行转移转化潜力评估,及时筛选出易于转让或许可的专利开展针对性的产业化运营。
Abstract
[Purpose/Significance] Using the dynamic characteristics of patents to identify their potential for technology transfer will help universities and research institutes to carry out patent grading management and operation, and promote the industrialization of patented technologies. [Method/Process] Patent characteristics present dynamic evolution in its life cycle. Based on the dynamic patent citation network, this article constructs a dynamic and static patent technology transfer potential evaluation index system from the perspective of dynamic development; takes the dynamic characteristics of the transferred or licensed patent as the learning object and adopts the decision tree method to establish technology transfer prediction model and conducts an empirical model test. [Results/Conclusions] The influence of patents in the citation network has a greater role in its transfer and conversion potential. The empirical test of the transfer prediction model based on decision trees has a high predictive effect. By monitoring the dynamic characteristics of patents, the model is used to evaluate the transfer and conversion potential in a timely manner and screen out patents that are easy to transfer or license to carry out targeted industrialization operation.
关键词
专利 /
技术转移 /
社会网络分析 /
决策树
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Key words
patent /
technology transfer /
social network analysis /
decision tree
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