• Nidhi S. Shah
• Rachana Patel

Clustering is process of grouping the object based on their attributes and features such that the data objects that are similar or closer to each other are put in the same cluster. K-means is most popular clustering algorithm which partitioned the data but When the amount of data to be clustered is large and/or when data becomes available incrementally then incremental clustering procedures are used. This paper reviews how to handle incremental data efficiently and also remove the drawback of K-means Clustering Algorithm by using different approaches. In this review paper, analysis of different methodology of Incremental Clustering algorithm is done which improve the quality and accuracy of clusters.

Clustering, Data object, K-means clustering, Incremental Clustering

"Review Paper On Incremental K-means Clustering Approaches", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.2, Issue 3, page no.537-540, March-2015, Available :http://www.jetir.org/papers/JETIR1503025.pdf

"Review Paper On Incremental K-means Clustering Approaches", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.2, Issue 3, page no. pp537-540, March-2015, Available at : http://www.jetir.org/papers/JETIR1503025.pdf