基于文献大数据分析的人才创新能力感知方法研究

Innovation Ability Perception Methods of Talents Based on Big Data Analysis of Literatures

文章研究一种运用大数据技术手段,通过对海量科技文献数据进行细粒度和全方位信息融合关联,结合适当的人才评价指标体系,快速定位领域科技相关领域创新型人才的方法,弥补传统人工定性考察的短板。对基于科技文献大数据分析的人才创新能力自动感知方法的"采集—抽取—融合—感知"总体框架、4项关键技术进行了研究分析,并通过一个机器人研究领域的人才感知实例初步验证了方法的可行性。

In this paper,big data technology is used to merge the fine-grained and comprehensive information of the massive scientific and technological (S&T)literature data.Combining with the appropriate evaluation system,it can quickly locate the innovative talents in the fields of science and technology,and make up for the disadvantages of traditional artificial qualitative investigation.The overall framework and four key technologies of "acquisition-extraction-fusion-perception"of talents innovation capability automatic perception method are analyzed based on the big data analysis of S&T literatures.And the feasibility of the method is verified through an example of talents perception in robot research field.