Abstract: A computer implemented method for identifying substitute products for a target product via a distributor's product management computer system, the method includes: receiving, at a distributor's product management computer system, data representing a target product of interest to a user of the system, wherein the target product is described by a plurality of variable-value attributes associated therewith; processing the received data through a machine-learning-produced algorithm and thereby generating data representing a first set of substitute product candidates for the target product and wherein each substitute product candidate has a corresponding match-score that represents a degree of determined similarity between that substitute product candidate and the target product; transforming the generated data that represents the first set of substitute product candidates into data representing a refined set of substitute product candidates by processing the generated data utilizing a constraint-based algorithm;

Abstract: A product management computer system that can include one or more processors, and a computer-readable medium comprising instructions stored therein, which when executed by the processors, can cause the processors to: receive data representing a target product of interest to a user of the system, wherein the target product is described by a plurality of variable-value attributes associated; process the received data through a machine-learning-produced algorithm and generating data representing a first set of substitute product candidates for the target product and wherein each substitute product candidate has a corresponding match-score that represents a degree of determined similarity between that substitute product candidate and the target product; transform the generated data that represents the first set of substitute product candidates into data representing a refined set of substitute product candidates by processing the generated data utilizing a constraint-based algorithm; and output data representing

Abstract: A product management computer system that can include one or more processors, and a computer-readable medium comprising instructions stored therein, which when executed by the processors, can cause the processors to: receive data representing a target product of interest to a user of the system, wherein the target product is described by a plurality of variable-value attributes associated; process the received data through a machine-learning-produced algorithm and generating data representing a first set of substitute product candidates for the target product and wherein each substitute product candidate has a corresponding match-score that represents a degree of determined similarity between that substitute product candidate and the target product; transform the generated data that represents the first set of substitute product candidates into data representing a refined set of substitute product candidates by processing the generated data utilizing a constraint-based algorithm; and output data representing