Patent ID: 11914621
Assignee: KOMODO HEALTH
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method performed by at least one processor, the method comprising:
obtaining pairs of training records for training an entity resolution model, wherein the pairs of training records comprise a first pair of training records, wherein the first pair of training records comprises a first record that indicates a first set of values for a first attribute and a second record that indicates a second set of values for the first attribute;
determining a set of association metrics corresponding to the pairs of training records at least by:
identifying a first value of the first set of values;
determining a first set of individual association metrics corresponding respectively to comparisons between the first value of the first set of values and each value of the second set of values;
executing a first-level reduction operation for the first set of individual association metrics, across the second set of values, to generate a first reduced association metric;
storing the first reduced association metric in a set of reduced association metrics;
identifying a second value of the first set of values;
determining a second set of individual associate metrics corresponding respectively to comparisons between the second value of the first set of values and each value of the second set of values;
executing the first-level reduction operation for the second set of individual association metrics, across the second set of values, to generate a second reduced association metric;
storing the second reduced association metric in the set of reduced association metrics;
excluding the first value and the second value, determining a presence of any more values in the first set of values;
based on determining that no more values are present in the first set of values, executing a second-level reduction operation for the set of reduced association metrics across the first set of values to generate a set of association metrics corresponding to the first pair of training records; and

applying a machine learning algorithm to the set of association metrics corresponding to the pairs of training records to train the entity resolution model.