| 基于专利分析的产学研合作特征与关系预测研究——以区域装备制造业为例 |
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| 引用本文： | 孙晓玲,庄伟华,李冰,陈娜.基于专利分析的产学研合作特征与关系预测研究——以区域装备制造业为例[J].科学与管理,2020,40(1):31-40. |
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| 作者姓名： | 孙晓玲 庄伟华 李冰 陈娜 |
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| 作者单位： | 大连理工大学科学学与科技管理研究所,辽宁大连116024;大连理工大学科学学与科技管理研究所,辽宁大连116024;大连理工大学科学学与科技管理研究所,辽宁大连116024;大连理工大学科学学与科技管理研究所,辽宁大连116024 |
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| 基金项目： | 国家自然科学基金青年项目（71704019）;辽宁省社科规划基金项目（L17CGL009） |
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| 摘 要： | 以产学研合作申请专利为研究对象,从合作主体、合作技术等方面对装备制造业的产学研合作特征进行分析,并利用网络表示学习算法node2vec进行合作预测研究。以辽宁、江苏、广东和北京的装备制造业为例进行对比分析,结果表明:各省市专利增长体量及申请人组成存在较大差异,发展缓慢省市的产学研合作局限在小团体内部,与其他区域相比校企合作较少;在技术特征中,不同省市的发展既各有侧重点,又有相同之处;最后通过合作预测发现最具有合作潜力的机构,为促进产学研合作提供决策支持。
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| 关 键 词： | 产学研合作 专利分析 网络表示学习 合作预测 |
Research on Characteristics and Cooperation Prediction of Industry-University-Research Institute Collaboration Based on Patents in Regional Equipment Manufacturing Industry |
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| Authors: | SUN Xiaoling ZHUANG Weihua LI Bing CHEN Na |
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| Institution: | (Institute of Science of Science and S&T Management,Dalian University of Technology,Dalian 116024,China) |
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| Abstract: | Using cooperative patent applications of industry,university and research institute as the research objects,the characteristics of technology evolution are analyzed from the aspects of cooperative network,cooperative technology,and cooperative prediction is studied by using network representation learning algorithm node2vec.Taking equipment manufacturing industry as an example,the results show:there are great differences in the volume of patent growth and the composition of applicants among provinces.The industry-university-research cooperation of provinces with slow development is confined to small groups,and the cooperation between universities and industries is less than that of other regions.Among the technical characteristics,the developments of different provinces have their own emphasis and similarities.Finally,through cooperation prediction,the most potential cooperative organizations are discovered,in order to provide support for promoting cooperation between industry and university. |
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| Keywords: | industry-university-research cooperation patent analysis network representation learning collaboration prediction |
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