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[目的 /意义]传统作者共引分析(ACA)方法将领域发展视为一个整体,忽略领域发展期间的变化,导致知识图谱解读会产生一定的偏差。本文旨在引入时间变量,找出领域发展期间的转变关键节点,并以此作为时间切片的划分依据,利用ACA绘制每个时间切片内部的知识图谱,观察领域内的子领域发展与核心作者的变化。[方法 /过程]首先通过作者的年度发文比例对时间切片进行选取,借鉴经济学均线理论对曲线做平滑处理,选取曲线变化度较高的年份作为转变节点切割时间段,并对每个时间切片内进行ACA的运算与结果分析。[结果 /结论]结果显示,随着时间的变迁,领域知识图谱发生了相应的变化,利用作者发文比例选择时间切点进行综合时间切片的作者共引分析提高了聚类结果的群聚性,且有助于挖掘出科学共同体的更多细节。
[Purpose / Significance] The traditional method of co-cited analysis (ACA) takes the development of the field as a whole and neglects the changes during the development of the field, resulting in some deviations in the interpretation of the knowledge map. This paper aims to introduce time variables to identify key nodes in the transformation of the field of development and use it as the basis for the division of time slices, using ACA to draw the knowledge map of each time slice, to observe the development of sub-fields and core authors in the field Variety. [Methods / Processes] Firstly, the author selects the time slices by the proportion of the annual papers and draws a smoothing curve by using the theory of economic averaging. The year with a higher degree of curve variation is selected as the cutting node of the transition nodes and the slices are sliced at each time ACA within the operation and result analysis. [Result / Conclusion] The results showed that the domain knowledge map changed correspondingly with the passage of time. The co-cited analysis of author’s author’s choice of time-point for comprehensive time slicing improved the cluster clustering results, And help dig out more details of the scientific community.