Web clustering is a data mining technique, which is a demanding field of research in which its latent applications create their own special requirements. The K-means is a widely used partitioned clustering method. The benchmark K-means clustering algorithm is sensitive to the selection of the initial centroids and may converge to a local minimum of the criterion function value. K-means clustering utilizes an iterative procedure that converges to local minimum. This local minimum is highly sensitive to the selected initial partition for the K-means clustering.