Kakinada Institute of Engineering and Technology for Women
Abstract
Clustering is the unproven classification of data items, into groups known as clusters. The clustering problem has been discussed in many area of research in many disciplines; this reflects its huge usefulness in the field of data analysis. However, clustering may be a difficult problem statistically, and the differences in assumptions in different disciplines made concepts and methodologies slow to occur. This paperpresentstaxonomy of clustering techniques, and recent advances in graphtheorytic approach. We also describe some important applications of clustering algorithms such as image segmentation, object recognition, and information retrieval
