Patent ID: 6519591
Filing Date: 2003-02-11
Classification: G06F,Y10S

Abstract:
A method for performing clustering within a relational database management system to group a set of n data points into a set of k clusters, each data point having a dimensionality p, the method comprising the steps of:establishing a first table, C, having 1 column and p*k rows, for the storage of means values; establishing a second table, R, having 1 column and p rows, for the storage of covariance values; establishing a third table, W, having w columns and k rows, for the storage of w weight, values; establishing a fourth table, Y, having 1 column and p*n rows, for the storage of values; and executing a series of SQL commands implementing an Expectation-Maximization clustering algorithm to iteratively update the means values, covariance values and weight values stored in said first, second and third tables; said step of executing a series of SQL commands implementing an Expectation-Maximization clustering algorithm includes the step of calculating a Mahalanobis distance for each of said n data points by using SQL aggregate functions to join tables Y, C and R.