识别核心专利的粗糙集理论模型  

Core Patent Identification Based on Rough Set Theory

作　　者：袁润[1] 钱过[2] 

机构地区：[1]江苏大学图书馆,镇江212013 [2]江苏大学科技信息研究所,镇江212013

出　　处：《图书情报工作》2015年第2期123-130,共8页Library and Information Service

基　　金：国家社会科学基金项目"图书馆知识发现服务的功能定位和建设策略研究"(项目编号:14BTQ018);江苏省哲学社会科学规划基金重点项目"数字环境下图书馆生态与服务变革研究"(项目编号:12TQA002)研究成果之一

摘　　要：[目的/意义]研究应用粗糙集理论分析专利信息的可行性及其方法,建立识别核心专利的粗糙集理论模型。[方法/过程]综述国内外研究核心专利识别的相关文献,确定包含8个指标的核心专利识别指标体系,再用粗糙集理论分析专利信息数据,确定各指标的权重系数,按照计算的核心专利综合指数(CICP)大小将某特定技术领域的专利信息序列分为核心专利、关键专利、重要专利和一般专利。[结果/结论]以通信领域的976件专利数据为分析样本,运用本文核心专利识别模型识别出11件核心专利,其中包含获得中国专利奖的专利,核心专利识别结果在一定程度上表明核心专利识别模型的可行性和科学性;本文核心专利识别模型具有一般性,可应用于分析研究专利价值及其重要性。[ Purpose/significance] This paper aims to study the feasibility and the method of analyzing patent infor- mation based on the rough set theory, and establish a rough set theory model to identify the core patent.[ Method/ process ] Through a relevant literature core patent recognition in China and abroad, determines the system of core patent i- dentification index, which includes 8 indicators, and then analyzes the patent information data using the rough set theory, and determines the weight coefficient of each index. According to the comprehensive index of the core patent calculation （CICP）, the size of patent information sequence of a particular technology area is divided into the core patent, key pa- tent, important patent and general patent. Taking 976 patents in the field of data communications as the sample identified 11 pieces of core patent, including patents which have won the Chinese patent awards. It proves the scientific nature and feasibility of the core patent identification model.[ Result/conclusion] The patent information recognition model is gener- al, and can be applied to the analysis of the research on patent value and importance.

关 键 词：核心专利 专利指标 层次分析法 粗糙集 

分 类 号：G353.1[文化科学—情报学] G306