Overview of Different Data Clustering Algorithms for Static and Dynamic Data Sets

Abstract

Data mining is the process of extracting meaningful information from a large set of data. Data clustering is one of the major techniques used in data mining. These techniques will group related data in to identical groups. Data clustering is an unsupervised data analysis and data mining technique; it generates meaningful views from an inherent structure of data. Hundreds of clustering algorithms have been developed by researchers from a number of different scientific disciplines. Data may be static or dynamic. This paper focussed on different clustering algorithms for static and dynamic datasets.