Survey of Clustering Applications

Data mining is the process of collecting and analyzing useful patterns from huge amount of data, it has five major functions, clustering is one of them. In clustering, we make clusters of same data. The items in one group of cluster are alike while different from items which are in some other group of cluster. In image segmentation clustering approach is used for making segments of images and identifying the disease, for this purpose the Fuzzy C-means algorithm is used. Clustering is used in social network analysis using collaborative filtering recommendation, in which memory-based and model-based algorithms are used. K-means algorithm is used in credit card fraud detection for identifying the clusters. It works along the HMM model for identifying credit card frauds. In medical world for disease analysis an improved Fuzzy C-means algorithm which is termed as 3SW-FCM algorithm is used which can analyze the characteristics of disease and provide an accurate base for doctor’s diagnosis. Greedy Agglomerative technique is a clustering category used for combining objects together grounded on resemblance which is used in grouping with respect to Reference Matching of High-Dimensional records. Index Terms Data Mining, Clustering, Social Network Analysis, Image Segmentation, Clustering applications, survey