专利布局相关性及专利权人关系辨识研究——以云计算行业为例

发布时间：2018-06-10 16:27

本文选题：加权二分图 + Pearson相关系数　；参考：《情报杂志》2016年04期

【摘要】：[目的/意义]如何利用专利数据定量地分析专利权人之间的专利布局相关性借以发现彼此之间的关系已经成为研究热点之一。尽管众多学者从不同角度对这一问题展开了相关研究,但尚存在一些不足之处。如何在兼顾专利权人自身技术资源和行业各技术领域资源配比的前提下度量专利布局相关性成为亟待解决的问题。[方法/过程]选择USPTO专利数据库中在云计算领域拥有7项以上发明专利的专利权人作为研究对象,利用加权二分图投影算法计算专利权人的专利资源分配相似性,然后站在整个云计算行业视角,利用Pearson相关性分析方法计算专利权人的专利布局相关系数。[结果/结论]通过专利布局相关性分析,专利权人可以更准确地识别其与同行之间的关系,进而挖掘出潜在竞争对手、未来合作伙伴等有价值信息,更为专利权人未来的技术创新布局提供指导建议。
[Abstract]:Objective / significance: how to use patent data to quantitatively analyze the correlation of patent layout among patentees to find out the relationship between each other has become one of the research hotspots. Although many scholars have carried out research on this issue from different angles, there are still some shortcomings. How to measure the dependence of patent layout on the premise of taking account of the patentee's own technical resources and the matching of technical resources in various fields of the industry has become an urgent problem to be solved. [method / process] the patentee who has more than 7 invention patents in cloud computing field in USPTO patent database is selected as the research object, and the similarity of patent resource allocation among patentees is calculated by weighted dichotomy projection algorithm. Then from the perspective of the whole cloud computing industry, Pearson correlation analysis method is used to calculate the patent layout correlation coefficient of the patentee. [results / conclusion] through the patent layout correlation analysis, the patentee can more accurately identify the relationship between the patentee and its peers, and then excavate valuable information such as potential competitors, future partners, etc. More patentee's future technological innovation layout provides the guidance suggestion.
【作者单位】：上海理工大学管理学院;华东交通大学经济管理学院;
【基金】：江西省高校人文社会科学研究项目“中国轨道交通领域专利布局相关性及专利权人关系辨识研究”(编号:TQ1502)研究成果之一国家自然科学基金项目“基于供需网(SDN)基本特征理念的企业合作优化模型方法研究”(编号:71171135)研究成果之一;国家自然科学基金项目“废弃电子产品回收再利用网络组织及其治理研究”(编号:71262011)研究成果之一;国家自然科学基金项目“企业知识与员工知识贡献度集成评价研究”(编号:71301068)研究成果之一
【分类号】：G306;G353.1

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