Measuring technological distance for patent mapping
Measuring technological distance for patent mapping
复制标题
测量专利映射的技术距离
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
Jianxi Luo
中科院分区：
文献类型：
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作者：
B. Yan;Jianxi Luo
最近的信息科学文献中提出了利用专利数据库和专利分类信息构建技术领域网络地图的案例，旨在帮助竞争情报分析和创新决策。构建这样的专利网络需要适当衡量专利分类系统中不同类别专利之间的距离。尽管文献中存在各种距离度量，但尚不清楚如何一致地评估和比较它们，以及选择哪些距离度量来构建专利技术网络图。这种模糊性限制了此类技术地图的开发和应用。在此，我们建议通过分析所得专利网络图结构特性的差异和相似性来比较替代距离度量并确定更好的距离度量。使用 1976 年至 2006 年的美国专利数据和国际专利分类 (IPC) 系统，我们比较了 12 个代表性距离度量，这些度量量化了领域间知识库的邻近性、领域交叉多样化的可能性或创新主体的频率，以及同一专利中专利类别的共现。我们的比较分析表明，基于归一化共指和发明人多元化可能性测度的专利技术网络图是最好的代表。
Recent works in the information science literature have presented cases of using patent databases and patent classification information to construct network maps of technology fields, which aim to aid in competitive intelligence analysis and innovation decision making. Constructing such a patent network requires a proper measure of the distance between different classes of patents in the patent classification systems. Despite the existence of various distance measures in the literature, it is unclear how to consistently assess and compare them, and which ones to select for constructing patent technology network maps. This ambiguity has limited the development and applications of such technology maps. Herein, we propose to compare alternative distance measures and identify the superior ones by analyzing the differences and similarities in the structural properties of resulting patent network maps. Using United States patent data from 1976 to 2006 and the International Patent Classification (IPC) system, we compare 12 representative distance measures, which quantify interfield knowledge base proximity, field‐crossing diversification likelihood or frequency of innovation agents, and co‐occurrences of patent classes in the same patents. Our comparative analyses suggest the patent technology network maps based on normalized coreference and inventor diversification likelihood measures are the best representatives.
影响因子：
3.9
作者：
L. Leydesdorff;D. Kushnir;Ismael Rafols
通讯作者：
L. Leydesdorff;D. Kushnir;Ismael Rafols