识别核心专利的粗糙集理论模型

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。

Core Patent Identification Based on Rough Set Theory

Purpose/significance] This paper aims to study the feasibility and the method of analyzing patent information 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 identification 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 patent, 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 general, and can be applied to the analysis of the research on patent value and importance.