在"数据爆炸"的当代，数据的价值与日俱增，数据创造价值，数据科学作为一门目前全国最火爆的学科，其目的是从大量数据中提取出有价值的信息用于生产活动。文章基于CiteSpace采用文献计量法，对CNKI和Web of Science两大通用主流文献库进行分析，总结了数据科学领域国内外近十五年研究热点与技术前沿的推进情况。研究结果显示，该领域的当前热点有卷积神经网络等，其热点算法有分类算法，如支持向量机，热点框架有PaddlePaddle等。文章还比较了近年国内外机器学习研究的侧重与发展规模，积极探讨了数据科学基础技术的研究热点，为该领域今后研究提供了方向借鉴。
Research Hotspot and Advance of the Frontier of Data Science at Home and Abroad—Visualization Analysis of CNKI and WOS Literature Based on CiteSpace
In the modern era of"data explosion",the value of data is increasing day by day,and data creates value.Data science,as the most popular subject in China,aims to extract valuable information from a large number of data for production activities.In this paper,based on CiteSpace,the bibliometrics method is used to analyze two general mainstream bibliothems,CNKI and Web of Science,and summarize the advancement of research hotspots and technological frontiers in the field of Data Science at home and abroad in the past 15 years.The research results show that the current hotspots in this field include Convolutional Neural Networks,hotspot algorithms include classification algorithms such as Support Vector Machines,and hotspot frameworks include PaddlePaddle and so on.This paper also compares the focus and development scale of Machine Learning research at home and abroad in recent years,and actively discusses the research hotspot of Data Science basic technology,and provides a reference for future research in this field.
国家科技期刊平台
NSTL
万方数据
