Emergence of modern techniques for scientific data collection has resulted in large scale
accumulation of data pertaining to diverse fields. Conventional database querying methods …

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

Clustering is the process of grouping similar data into a set of clusters. Cluster analysis is
one of the major data analysis techniques and k-means one of the most popular partitioning …

Clustering technique is used to put similar data items in a same group. K-mean clustering is
a common approach, which is based on initial centroids selected randomly. This paper …

Data clustering helps one discern the structure of and simplify the complexity of massive
quantities of data. It is a common technique for statistical data analysis and is used in many …

K-means clustering is a popular clustering algorithm based on the partition of data.
However, K-means clustering algorithm suffers from some shortcomings, such as its …

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 …