Devarakonda Sitaram, Korobskiy Dmitriy, Warnow Tandy, Chacko George
Netelabs, NET ESolutions Corporation, McLean, VA.
Dept of Computer Science, University of Illinois Urbana-Champaign, Champaign IL.
Scientometrics. 2020 Oct;125(1):271-287. doi: 10.1007/s11192-020-03624-0. Epub 2020 Jul 20.
Computer science has experienced dramatic growth and diversification over the last twenty years. Towards a current understanding of the structure of this discipline, we analyze a large sample of the computer science literature from the DBLP database. For insight on the features of this cohort and the relationship within its components, we have constructed article level clusters based on either direct citations or co-citations, and reconciled them with major and minor subject categories in the All Science Journal Classification (ASJC). We describe complementary insights from clustering by direct citation and co-citation, and both point to the increase in computer science publications and their scope. Our analysis reveals cross-category clusters, some that interact with external fields, such as the biological sciences, while others remain inward looking. Overall, we document an increase in computer science publications and their scope.
在过去二十年中,计算机科学经历了显著的发展和多样化。为了深入了解该学科的结构,我们分析了来自DBLP数据库的大量计算机科学文献样本。为了洞察这一群体的特征及其组成部分之间的关系,我们基于直接引用或共引构建了文章级别的聚类,并将它们与《全科学期刊分类》(ASJC)中的主要和次要主题类别进行了协调。我们描述了直接引用聚类和共引聚类的互补性见解,两者都表明计算机科学出版物及其范围在增加。我们的分析揭示了跨类别聚类,其中一些与外部领域(如生物科学)相互作用,而另一些则保持内向性。总体而言,我们记录了计算机科学出版物及其范围的增加。