期刊共被引相似性测度问题的实证研究

An Empirical Research of the Similarity Measures for Journal Co-citation Analysis

在共被引分析中,还有诸多问题未解决,如原始数据是否需要标准化,选择何种相似性测度方式更为准确可靠。从理论分析和实证研究两个方面探讨期刊共被引相似性测度问题,得出期刊共被引分析是否需要将数据进行标准化处理的结论及切比雪夫距离是期刊共被引分析中相似性测度的理想选择。

Should the original co-citation data be normalized？ Which similarity measure is a more appropriate one？ These are some unsolved issues of co-citation analysis. From theoretical analysis and empirical study, the paper concludes about whether the original data should be normalized or not, and supports that the Chebychev distance is a better similarity measure for joumal co-citation.