The k-Means clustering algorithm is an old algorithm that has been intensely researched
owing to its ease and simplicity of implementation. Clustering algorithm has a broad …

In the field of data mining, clustering is a technique where millions of data points are
grouped together to form a cluster. Data of same class are grouped together. K-Means …

Abstract k-means is one of the most widely used partition based clustering algorithm. But the
initial centroids generated randomly by the k-means algorithm cause the algorithm to …

K-means clustering algorithm clusters datasets according to the certain clustering number k.
However, k cannot be confirmed beforehand. A new clustering validity index was designed …

Big data has become famous to process, store and manage massive volumes of data.
Clustering is an essential phase in big data analysis for many real-life application areas …

Cluster analysis is a major technique for classifying a „mountain‟ of information into
manageable meaningful piles. It is a data reduction tool that creates subgroups that are …

Partition-based clustering technique is one of several clustering techniques that attempt to
directly decompose the dataset into a set of disjoint clusters. K-means algorithm …

Clustering is the process of grouping the data based on their similar properties. Meanwhile,
it is the categorization of a set of data into similar groups (clusters), and the elements in each …

The k-means algorithm is one of the most widely used methods to partition a dataset into
groups of patterns. However, most k-means methods require expensive distance …

K-means is an effective clustering technique used to separate similar data into groups based
on initial centroids of clusters. In this paper, Normalization based K-means clustering …