%0 Journal Article
%T 贝叶斯网络研究现状与发展趋势的文献计量分析<br>The Bibliometric Analysis of Current Studies and Developing Trends on Bayesian Network Research
%A 肖中正
%A 努尔布力
%A 刘宏阳
%J Computer Science and Application
%P 493-504
%@ 2161-881X
%D 2020
%I Hans Publishing
%R 10.12677/CSA.2020.103052
%X <div style=\"text-align:justify;\">
	<span style=\"font-size:14px;\">本文以web of science中近10年2930篇与贝叶斯网络有关的文献为研究对象，基于文献计量内容分析方法系统地回顾了国内外在贝叶斯网络领域的关注点、研究脉络的发展规律、存在的共性与差异性和研究现状。研究发现，截至目前，特别是在神经网络盛行的现在，贝叶斯网络可以凭借其具有较强的数学可解释性，在智能计算领域的贡献不断深化且具有极大的潜力。分析结果有助于为我国贝叶斯网络研究领域的学者提供研究现状及进展的参考。<br />
In this paper, 2,930 literatures related to Bayesian network in the recent 10 years in the web of science were taken as the research object. Based on the literature metrological content analysis method, the focus, development rules of research context, existing commonalities and differences, and research status at home and abroad were systematically reviewed. The study found that, as of now, especially in the prevalence of neural networks, Bayesian networks can be deepened and have great potential because of their strong mathematical interpretability. The analysis results are helpful to provide reference for the research status and progress of scholars in the field of Bayesian network research in China.</span> 
</div>
%K 贝叶斯网络，图谱分析，CiteSpace，研究脉络<br>Bayesian Network
%K Map Analysis
%K Citespace
%K Research Context
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=34587