Computer implemented scalable, incremental and parallel clustering based on weighted divide and conquer

A technique that uses a weighted divide and conquer approach for clustering a set S of n data points to find k final centers. The technique comprises 1) partitioning the set S into P disjoint pieces S 1 , . . . , S P ; 2) for each piece S 1 , determining a set D 1 of k intermediate centers; 3) assigning each data point in each piece S i to the nearest one of the k intermediate centers; 4) weighting each of the k intermediate centers in each set D 1 by the number of points in the corresponding piece S 1 assigned to that center; and 5) clustering the weighted intermediate centers together to find said k final centers, the clustering performed using a specific error metric and a clustering method A.