基于专利信息评价和挖掘智能机器人领域技术创新人才——主成分分析法PCA的视角

Evaluating and Mining the Technological Innovative Talents in The Field of Intelligent Robots Based on Patent Information——The Perspective of Principal Component Analysis (PCA)

摘要:

专利是衡量技术创新能力和水平的重要指标,从技术研发角度,通过对发明人的专利信息分析可以揭示技术创新者的科研水平和竞争力。以智能机器人领域为例,以DI数据库检索清洗出申请量排名前100的发明人为研究对象,基于专利信息构建技术创新人才评价指标体系,结合主成分分析法,筛选指标特征。对这些发明人的技术创新水平进行统计分析和综合评价,通过DDA分析平台共现矩阵和聚类分析,挖掘技术创新人才及团队。

Abstract:

Patent is an important index to measure the ability and level of technological innovation. From the angle of technology research and development, the research level and competitiveness of the innovators can be revealed through the inventor patent information analysis. Taking the field of intelligent robot as an example, using the DI database to retrieve and clean the first 100 inventors in the number of applications, construct the evaluation index system of technical innovation talents based on the patent information. Combining the principal component analysis method to select the index characteristics. It makes a statistical analysis and comprehensive evaluation on the technological innovation level of these inventors. Through DDA analysis platform, using co-occurrence matrix and cluster analysis map to dig technical innovation talents and teams.