基于知识元语义组合差异的专利新颖性细粒度测度方法——以工业机器人领域为例  被引量:2

Fine-grained Measure Method of Patent Novelty Based on Knowledge Element Semantic Combination Differences:Taking Industrial Robotics for Example

在线阅读下载全文

作  者:唐晓波[1,2] 朱婧 杜鑫 Tang Xiaobo

机构地区:[1]武汉大学信息系统研究中心,湖北武汉430072 [2]武汉大学信息管理学院,湖北武汉430072

出  处:《情报理论与实践》2023年第11期154-163,195,共11页Information Studies:Theory & Application

基  金:国家社会科学基金重大项目“基于大数据的科教评价信息云平台构建和智能服务研究”的成果之一,项目编号:19ZDA349。

摘  要:[目的/意义]科技成果的新颖性是科技成果价值的重要属性,测度专利新颖性有利于从众多专利中筛选出与以往技术存在显著差异的专利,对专利评价具有重要意义。[方法/过程]提取专利方案、功效、应用以及“方案—功效”“方案—应用”和“功效—应用”等知识元语义组合;计算各类知识元语义组合差异,包括语义差异、频次高低、年龄大小、IPC分类号差异;测度专利整体新颖性和知识元语义组合新颖性,并采用工业机器人领域发明专利数据进行实验。[结果/结论]所提出的方法能够有效实现专利新颖性细粒度测度。研究成果丰富了专利新颖性测度方法,有助于对专利新颖性进行更客观、全面、及时、细粒度的审查与评价。[Purpose/significance]The novelty of scientific and technical achievements is an important attribute of their value.Measuring patent novelty is useful for screening out patents that are significantly different from previous technologies from a large number of patents,which is important for patent evaluation.[Method/process]Extract knowledge element semantic combination such as solution,efficacy,application,“solution-efficacy”“solution-application”and“efficacy-application”.Calculate the differences of various knowledge element semantic combination,including semantic differences,frequency,age and IPC classification number differences.Measure the overall patent novelty and knowledge element semantic combination novelty.The patent data from industrial robotics are used for experiments.[Result/conclusion]The experimental results show that the method proposed in this study can effectively realize the fine-grained measurement of patent novelty.This study enriches the patent novelty measurement method and helps to examine and evaluate patent novelty more objectively,comprehensively,timely and fine-grained.

关 键 词:专利 新颖性测度 知识元 语义组合差异 细粒度 

分 类 号:G255.53[文化科学—图书馆学] TP242.2[自动化与计算机技术—检测技术与自动化装置]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象