Graph based Clustering Techniques

Clustering is widely used technique to find hidden, meaningful patterns in the given dataset, called as clusters. It is grouping of data into groups of similar objects. The objective is that the objects within a group should be similar to one another and different from the objects in other groups. Clustering plays an excellent role in data mining applications, biology, science, pattern recognition, social networking, machine learning, web analysis, CRM, marketing, medical diagnostics, and many others. A variety of clustering algorithms have emerged that meet these requirements and were successfully applied to many data mining and pattern recognition problems. Due to their great representational power, Graphs can handle huge databases with large attributes. Hence Graphs play a vital role in clustering applications