基于论文和专利数据的研究前沿挖掘研究——以智能网联汽车领域为例

Mining the Cutting Edge Based on Scientific Papers and Patents—A Case Study on Intelligent and Connected Vehicle

[目的/意义]对比论文数据和专利数据的特征指标,识别热点、新兴、潜在和消亡研究前沿主题。[方法/过程]利用LDA主题模型,对智能汽车领域相关的论文数据和专利数据进行主题提取,计算两个数据源下各主题的强度和主题新颖度并进行对比分析。[结果/结论]本文识别出路径规划技术等热点研究前沿6个、智能计算等新兴研究前沿2个、安全认证技术等潜在研究前沿6个、车载平台等消亡研究前沿6个。本文在前沿识别方法上进行了创新,有效识别出领域内研究前沿并进行分类,为相关机构和研究人员提供借鉴。

[Purpose/significance]By comparing the characteristic indexes of the paper data and the patent data,this paper identifies the hot,emerging,potential and weak research front topics.[Method/process]LDA model is used to extract the theme of related papers and patents in the field of intelligent and connected vehicle.The intensity and novelty of each topic were calculated and compared between the two data sources.[Result/conclusion]This study identifies 6 hot cutting edges such as path planning technology,2 emerging cutting edges such as intelligent computing,6 potential cutting edges such as security authentication technology and 6 weak cutting edges such as vehicle-borne platform.This research contributes on the methods of data source and frontier identification,effectively identifies and classifies the scientific front in the field,and provides reference for related institutions and researchers.