Approaches to Cluster Analysis

Many data mining methods rely on some concept of the similarity between pieces of information encoded in the data of interest. Various names have been applied to these clustering methods, depending largely on the field of application in data science. For example, in biology the term “numerical taxonomy” is used [Thorel et al., 1990], in psychology the term Q analysis is sometimes employed, market researchers often talk about “segmentation” [Arimond/Elfessi, 2001] and in the artificial intelligence literature, unsupervised pattern recognition is the favored label [Everitt et al., 2001, p. 4].