期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2015
卷号：6
期号：6
页码：5308-5312
出版社：TechScience Publications
摘要：Similarity/dissimilarity measures in clustering algorithms play an important role in grouping data and finding out how well the data differ with each other. The importance of clustering algorithms in transportation data has been illustrated in previous research. This paper compares the effect of different distance/similarity measures on a partitional clustering algorithm kmedoid(PAM) using transportation dataset. A recently developed data mining open source software ELKI has been used and results illustrated.
