Evolving limitations in K-means algorithm in data mining and their removal

In the modern world large amount of information is stored in our database. These information are stored at different places in our data bases, therefore we have to develop some methods for extracting essential Information from these databases. Therefore we have to develop some methods for extracting essential Information from these databases; data mining is the process of extracting this information. There are various types of algorithms in data mining process. From these algorithm k-means algorithm is evolved. K-means is very popular because it is conceptually simple and is computationally fast and memory efficient but there are various types of limitations in k means algorithm that makes extraction some what difficult. In this paper we are discussing