用于知识流动测度的专利引文指标分析  

Analysis of Patentcitation Indicators for Knowledge Flow Measurement

作　　者：祁延莉[1] 李婧[2] 

机构地区：[1]北京大学信息管理系,北京100871 [2]中国石化石油工程技术研究院,北京100028

出　　处：《中国基础科学》2014年第2期25-33,共9页China Basic Science

摘　　要：专利引证关系反映了国家或企业间知识流动的轨迹,专利引文数据是知识流动测度的重要证据。本文对基于专利引文的知识流动测度指标进行了分析与论证。这些指标包括专利施引量、专利被引量、专利被引的延展性、专利施引的散源性、专利引用时滞、专利引用比例、专利引用频率、专利相对引用频率、技术相似度和基于专利引用的知识流动模型。Patent citations reflect the track of knowledge flows between countries or companies,the data of patent citations are substantial evidences of technological knowledge flows. This paper discusses the kinds of measurement indicators based on patent citation, including times of citing patent,times of cited patent,citation generality, citation originality, citation lag, citation share,citation frequency,relative citation frequency,and patent technological proximity. The knowledge flow model based on patent citations is illustrated with examples.

关 键 词：知识流动测度 引文分析 专利引文 专利引文指标 知识流动模型 

分 类 号：G35[文化科学—情报学]