Two phase hierarchical clustering algorithm for group formation in data mining

Data clustering is often one of the first steps in data mining analysis. It identifies groups of related objects that can be used as a starting point for exploring further relationships. This technique supports the development of population segmentation models, such as demographic-based customer segmentation. This paper presents the development of two phase hierarchical clustering algorithm for group formation. Applications of the algorithm for product–customer group formation in customer relationship management are also discussed. As a result of computer simulations, suggested algorithm outperforms single link method and k-means clustering.