摘要
[目的/意义]探讨相关多维动态大数据特征以及在新兴产业技术预测分析中的作用,从而整合多维动态大数据信息知识,为新兴产业技术预测分析提供框架支持。[方法/过程]首先通过探究分析专利大数据、论文大数据、奖励大数据以及经济大数据各自的知识特征及优势互补,进而提出多维动态大数据关联模式架构。在此基础上,通过“人”和“事”的综合分析,量化给定产业技术的新兴指数。[结果/结论]实验结果表明,文章提出的预测分析框架充分利用了多维动态大数据信息较高的知识密度和广度,能够为新兴产业技术预测提供更为全面的多模态决策支持。
[Purpose/significance]The paper mainly discusses the characteristics of related multi-dimensional dynamic big data and its utilizations in the emerging technology prediction.This research helps to integrate multi-dimensional dynamic big data and then provide frame support for emerging technology prediction.[Method/process]This paper firstly proposes a multi-dimensional dynamic big data association structure by exploring and analyzing the knowledge characteristics and complementary advantages of patent big data,paper big data,reward big data and economic big data.On this basis,the emerging index of a given industrial technology is quantified through a comprehensive analysis of"people"and"things".[Result/conclusion]The experiment results shows that prediction and analysis framework proposed in this paper makes full use of multi-dimensional dynamic big data information,which has high knowledge density and breadth,and this can provide more comprehensive multi-modal decision support for emerging technology prediction.
作者
徐璐
潘禹辰
Xu Lu;Pan Yuchen(School of Information Resource Management,Renmin University of China,Beijing,100872)
出处
《情报资料工作》
北大核心
2023年第4期13-23,共11页
Information and Documentation Services
基金
国家社会科学基金重点项目“新时期产业技术情报分析方法体系研究”(批准号:21ATQ008)的研究成果之一。
关键词
新兴产业技术
多维动态大数据
关联模式架构
新兴指数
emerging technology
multi-dimensional dynamic big data
correlation structure
emerging index
