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作 者:张金柱[1] 施佳璐 章成志[1,2] Zhang Jinzhu;Shi Jialu;Zhang Chengzhi(Department of Information Management,School of Economics&Management,Nanjing University of Science&Technology,Nanjing 210094;Key Laboratory of Rich-media Knowledge Organization and Service of Digital Publishing Content,Institute of Scientific and Technical Information of China,Beijing 100038)
机构地区:[1]南京理工大学经济管理学院信息管理系,南京210094 [2]中国科学技术信息研究所富媒体数字出版内容组织与知识服务重点实验室,北京100038
出 处:《情报学报》2023年第10期1251-1264,共14页Journal of the China Society for Scientific and Technical Information
基 金:国家自然科学基金面上项目“基于专利多模态内容和交易数据的互补技术识别与挖掘研究”(72374103),“基于表示学习的专利信息语义融合与深度挖掘研究”(71974095);富媒体数字出版内容组织与知识服务重点实验室开放课题“面向融合出版的前沿技术发现研究”(ZD2022-10/02)。
摘 要:专利技术互补性作为各类组织进行技术创新的重要参考,近年来受到国内外学者的广泛关注。本文回顾了技术互补性概念的发展沿革,从产业/行业分类、专利分类、专利引用关系以及专利内容特征关联四个角度归纳其测度方法,最后综述专利技术互补性的多种应用。基于此,总结形成专利技术互补性的概念内涵,发现相关研究主要利用专利分类或专利引用网络来形成技术互补测度指标和方法,并主要应用于创新绩效因素判定、企业并购决策制定以及潜在合作伙伴发现等。未来,建议继续细化和具体化技术互补性概念,综合利用专利文本、图表、市场信息等多模异构数据,设计细粒度定量测度指标,引入深度学习等方法,提升专利技术互补测度的准确性,进一步拓宽专利技术互补性的应用范围,提升应用效果。As an important reference for technological innovation in various organizations,patent technology complementarity has recently received extensive attention from scholars worldwide.This paper first presents a review of the evolution of the technology complementarity concept and generalizes its measurement methods from four perspectives:industry/trade classification,patent classification,patent citation relationship,and patent content feature association.Then,various applications of patent technology complementarity are summarized.This review focuses on the concept of patent technology complementarity and indicates that relevant studies primarily use patent classification or a patent citation network to form technology complementarity measurement indices and methods,which are mostly applied in the innovation of the performance factor determination,enterprise of merger and acquisition(M&A)decision making,and potential partner discovery.In the future,we intend to continue to refine the technology complementarity concept,make comprehensive use of multimodal heterogeneous data such as patent text,chart,and market information,design fine-grained quantitative measurement indices,improve the accuracy of the patent technology complementarity measurement by introducing recently developed methods such as deep learning,and broaden the application effect and scope of patent technology complementarity.
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