26. A method of using a candidate selection system that includes at least a first trained machine learning system, the method comprising: receiving, by at least one processor-based system, a number of heuristic values each indicative of a strength of a respective pairing between two entities, the heuristic values generated by at least one machine learning system trained with at least a first entity and a second entity that are a historically successful pairing, and trained with a plurality of hypothetical alternative pairings between the first entity of the historically successful pairing and other entities of a first set of entities based at least in part on at least one value of each of at least one of a plurality of attributes associated with the second entity and based on at least one loosened constraint of a number of constraints applied to matches between the values of at least one of the attributes associated with the second entity; and executing, by the at least one processor-based system, a candidate selection algorithm which employs the received heuristic values and respective values for each of the plurality of attributes for each of a second set of entities to identify prospective candidates.
26. A method of using a candidate selection system that includes at least a first trained machine learning system, the method comprising: receiving, by at least one processor-based system, a number of heuristic values each indicative of a strength of a respective pairing between two entities, the heuristic values generated by at least one machine learning system trained with at least a first entity and a second entity that are a historically successful pairing, and trained with a plurality of hypothetical alternative pairings between the first entity of the historically successful pairing and other entities of a first set of entities based at least in part on at least one value of each of at least one of a plurality of attributes associated with the second entity and based on at least one loosened constraint of a number of constraints applied to matches between the values of at least one of the attributes associated with the second entity; and executing, by the at least one processor-based system, a candidate selection algorithm which employs the received heuristic values and respective values for each of the plurality of attributes for each of a second set of entities to identify prospective candidates. 32. The method of claim 26 wherein the hypothetical alternative pairings are indicative of an exact match between respective values of the first entity of the historically successful pairing and the entities of the first set of entities for less than all of the attributes of the plurality of attributes.