K-means Based Convex Hull Triangulation Clustering Algorithm

Abstract

As the variety of accessible web content grows, it becomes harder for users finding documents relevant to their interests. cluster is that the classification of an information set into subsets (clusters), so the info in every set (ideally) share some common attribute - usually proximity per some outlined distance live. we introduce Kmeans-Based Convex Hull Triangulation clustering algorithm (KBCHT) a new clustering algorithm that studies the given dataset to find the clusters. KBCHT algorithm can detect clusters without pre-determination of clusters number in datasets which contain complex non-convex shapes, different sizes, densities, noise and outliers.