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Using author tri-citation analysis to map knowledge domains in knowledge representations

机译：使用作者三引文分析在知识表示中映射知识域

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摘要

Purpose-Previous commonly used author co-citation analysis (ACA) methods have limited the ability to deal with accidental co-citation in constructing a raw co-citation matrix. Therefore, the purpose of this paper is to propose a new method, called author tri-citation analysis (ATA), to better map knowledge domains and depict scientific intellectual structures. Design/methodology/approach-Different from the previous method of using ACA that captures author co-citation relationships, the ATA method seeks tri-citation relationships among authors. Compared with ACA, ATA can ignore some accidental co-citation relationships between authors and can improve the accuracy of mapping knowledge domains. Findings-Although ATA does not mine more sub-fields than ACA does, the results of the empirical studies show that ATA, the newly proposed method, performs better in knowledge domain maps based on publications in the field of computer science. Research limitations/implications-The definition of ATA in this article is simple and still insufficiently informative. Many other pieces of information can be involved; for example, all authors' information, authors' sequence in the author list, reference published time and similar. These can be enhanced in future studies. Practical implications-This research will enrich the methods of mapping knowledge domains due to its new perspective. Social implications-Knowledge domain mapping is important to understand a discipline, and this research provides more potentialmethods for this, which benefits the performance of the maps. Originality/value-ATA can provide a methodological awareness for mapping knowledge domains. This value lies in not only a tri-citation perspective, but also author bibliographic tripling and author tri-operation perspectives ("tri-" perspectives).
机译：目的-以前常用的作者共同引用分析（ACA）方法在构建原始共同引用矩阵时限制了处理意外共同引用的能力。因此，本文的目的是提出一种称为作者三引文分析（ATA）的新方法，以更好地映射知识领域并描绘科学的知识结构。设计/方法/方法与以前使用ACA捕获作者共引关系的方法不同，ATA方法寻求作者之间的三引关系。与ACA相比，ATA可以忽略作者之间的一些偶然的共引关系，并可以提高映射知识域的准确性。结果尽管ATA不会比ACA挖掘更多的子字段，但是实证研究的结果表明，基于计算机科学领域的出版物，新提出的ATA在知识领域地图中的表现更好。研究局限性/含义-本文中ATA的定义很简单，但仍缺乏足够的信息。可能涉及许多其他信息。例如，所有作者的信息，作者列表中作者的顺序，参考出版时间等。这些可以在以后的研究中得到加强。实际意义-由于其新的视角，本研究将丰富映射知识领域的方法。社会意义-知识域映射对于理解一门学科很重要，这项研究为此提供了更多潜在方法，这有利于地图的性能。独创性/价值-ATA可以为映射知识领域提供一种方法上的意识。该价值不仅在于三引文的观点，还在于作者书目三倍论和作者三文法的观点（“ tri-”观点）。

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