期刊名称：Studia Universitatis Babes-Bolyai : Series Informatica
印刷版ISSN：1224-869X
出版年度：2006
卷号：LI
期号：01
页码：69-69
出版社：Babes-Bolyai University, Cluj-Napoca
摘要：This paper aims at presenting and comparing three clustering
algorithms in aspect mining: k-means (KM), fuzzy c-means (FCM) and hierarchical
agglomerative clustering (HAC). Clustering is used in order to
identify crosscutting concerns. We propose some quality measures in order
to evaluate the results and we comparatively analyze the obtained results on
two case studies.
