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| A Study on the Potential Collaborative Discovery of Industry-Academia-Research Based on Patent Documents |
| Fang Siyue1,2, Chen Fang1, Wang Xuezhao1,2 |
1.National Science Library, Chinese Academy of Sciences, Beijing 100190
2.Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190 |
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Abstract Using patent documents to construct an industry-academia-research collaboration network and identify potential industry-university-research collaboration can help increase efficiency. A link prediction and coupling analysis method based on patentee manual codes were introduced into the collaboration network. The similarity index of link prediction was used to calculate the path similarity of the patentee and cosine distance was used to calculate the content similarity of the patentee. A weighted fusion index was constructed by fusing path similarity and content similarity. Area Under Curve (AUC) was used to determine the weight of the fusion index, and the effect of the index was tested in the industry-academia-research collaboration network for the biopharmaceutical industry, using data from the years 2014 to 2018. The empirical results showed that when the ratio of path similarity and content similarity was 1∶9, the prediction result performed the best. The potential collaboration results predicted by the optimal algorithm can be used to support the decision-making of industry-university-research innovation subjects on future cooperation partners in the biopharmaceutical industry.
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Received: 24 November 2021
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1 张薇, 董瑜, 赵亚娟, 等. 产学研结合的国际比较[J]. 科学观察, 2008, 3(2): 5-11.
2 王超, 许海云, 方曙. 产学研潜在合作对象识别方法研究[J]. 科学学研究, 2018, 36(1): 101-113.
3 Suarez-Villa L. Invention, inventive learning, and innovative capacity[J]. Behavioral Science, 1990, 35(4): 290-310.
4 Hagedoorn J, Cloodt M. Measuring innovative performance: is there an advantage in using multiple indicators?[J]. Research Policy, 2003, 32(8): 1365-1379.
5 王秋玉, 曾刚, 吕国庆. 中国装备制造业产学研合作创新网络初探[J]. 地理学报, 2016, 71(2): 251-264.
6 方思越, 王学昭. 基于科研网络的潜在合作关系预测研究综述[J]. 情报工程, 2022, 8(1): 35-45.
7 Zhao D Z, Strotmann A. Evolution of research activities and intellectual influences in information science 1996-2005: introducing author bibliographic-coupling analysis[J]. Journal of the American Society for Information Science and Technology, 2008, 59(13): 2070-2086.
8 朱云霞, 魏建香. 基于共引网络的学者间潜在合作机会发现[J]. 西南民族大学学报(人文社科版), 2016, 37(9): 235-240.
9 陈卫静, 郑颖. 基于作者关键词耦合的潜在合作关系挖掘[J]. 情报杂志, 2013, 32(5): 127-131.
10 刘竟, 孙薇. 基于链路预测的潜在科研合作关系发现研究[J]. 情报理论与实践, 2017, 40(7): 88-92, 121.
11 林原, 刘海峰, 王海龙, 等. 基于表示学习的学者间潜在合作机会挖掘[J]. 情报杂志, 2019, 38(5): 65-70.
12 温芳芳. 基于专利权人-分类号耦合分析的潜在合作关系网络研究[J]. 情报学报, 2016, 35(12): 1265-1272.
13 王菲菲, 芦婉昭, 贾晨冉, 等. 基于论文-专利机构合作网络的产学研潜在合作机会研究[J]. 情报科学, 2019, 37(9): 9-16.
14 许海云, 隗玲, 庞弘燊, 等. 产学研潜在合作对象识别方法研究[J]. 情报学报, 2016, 35(5): 521-529.
15 冉从敬, 宋凯, 何梦婷, 等. 校企合作背景下高校前沿科研团队探测模型构建——以区块链技术领域为例[J]. 现代情报, 2020, 40(6): 46-54.
16 张斌, 马费成. 科学知识网络中的链路预测研究述评[J]. 中国图书馆学报, 2015, 41(3): 99-113.
17 Lorrain F, White H C. Structural equivalence of individuals in social networks[M]// Social Networks: A Developing Paradigm. Pittsburgh: Academic Press, 1977: 67-98.
18 Zhao J, Miao L L, Yang J, et al. Prediction of links and weights in networks by reliable routes[J]. Scientific Reports, 2015, 5: 12261.
19 吕琳媛, 周涛. 链路预测[M]. 北京: 高等教育出版社, 2013.
20 沈君, 高继平, 滕立. 德温特手工代码共现法: 一种实用的专利地图法[J]. 科学学与科学技术管理, 2012, 33(1): 12-16.
21 李文娟, 陈晶. 基于专利分析的我国生物制药产业技术周期预测[J]. 沈阳药科大学学报, 2018, 35(1): 73-77.
22 Zhang K R, Liu W Y. The current status, trend, and development strategies of Chinese biopharmaceutical industry with a challenging perspective[J/OL]. SAGE Open, 2020, 10(1). (2020-01-23). https://doi.org/10.1177/2158244020901529.
23 谢华玲, 陈芳, LiuCynthia, 等. 全球生物制药领域研发态势分析[J]. 中国生物工程杂志, 2019, 39(5): 1-10.
24 刘秋宏. 德温特专利权人代码编制研究及检索应用[J]. 科技创新导报, 2013, 10(4): 5-8, 11.
25 Valverde S, Cancho R F, Solé R V. Scale-free networks from optimal design[J]. Europhysics Letters, 2002, 60(4): 512-517.
26 温芳芳. 基于社会网络分析的专利合作模式研究[J]. 情报杂志, 2013, 32(7): 119-123.
27 张斌, 李亚婷. 学科合作网络链路预测结果的排序鲁棒性[J]. 信息资源管理学报, 2018, 8(4): 89-97. |
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