Mad Street Den, Inc.

Hariharan Chandrasekaran

Aravindakshan B

Sudarshan B

Aravindakshan Babu

Saurabh Agarwal

Sudarshan Babu

An optimized and efficient method of identifying one or more points within a dataset that are close to the centers of clumps similar records in a large, multi-element dataset uses Monte Carlo techniques to compute approximate clustering costs at significantly reduced computational expense. The inaccuracy caused by the approximate methods is also estimated, and if it is too high, the method may be repeated with a larger Monte Carlo sample size to improve accuracy. Portions of the algorithm that are independent are distributed among a number of cooperating computing nodes so that the full algorithm can be completed in less time.

Method and system for efficient clustering of combined numeric and qualitative data records

An optimized and efficient method of identifying one or more points within a dataset that are close to the centers of clumps similar records in a large, multi-element dataset uses Monte Carlo techniques to compute approximate clustering costs at significantly reduced computational expense. The inaccuracy caused by the approximate methods is also estimated, and if it is too high, the method may be repeated with a larger Monte Carlo sample size to improve accuracy.

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Chennai, India

Hariharan Chandrasekaran