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 …

Clustering analysis is the most significant step in data mining. This paper discusses the k-
means clustering algorithm and various distance functions used in k-means clustering …

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 …

Distance measures play an important role in cluster analysis. There is no single distance
measure that best fits for all types of the clustering problems. So, it is important to find set of …

K-means algorithm is a very popular clustering algorithm which is famous for its simplicity.
Distance measure plays a very important rule on the performance of this algorithm. We have …

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 …

Data Mining is the technique used to visualize and scrutinize the data and drive some useful
information from that data so that information can be used to perform any useful work. So …

Advances in recent techniques for scientific data collection in the era of big data allow for the
systematic accumulation of large quantities of data at various data-capturing sites. Similarly …

This paper presents a data clustering approach using modified K-Means algorithm based on
the improvement of the sensitivity of initial center (seed point) of clusters. This algorithm …