1. A computer-implemented method comprising: receiving from a retailer, by a configured computer system, a request for one or more recommended user sets that include indications of multiple specific users to which to provide product advertising for one or more products, wherein the request indicates the one or more products but does not include the one or more user sets; obtaining, by the configured computer system, a plurality of user sets from one or more automated user recommendation systems, the plurality of user sets having been generated using multiple different user models; and in response to the receiving of the request, using ensemble learning to automatically select, by the configured computer system and from the plurality of user sets, one or more most relevant user sets for the one or more products, the selected one or more user sets indicating multiple users, wherein the using of the ensemble learning includes automatically selecting the one or more most relevant user sets from the plurality of user sets based, at least in part, on information regarding user behavior collected from user activity subsequent to previous recommendations; and electronically communicating the selected one or more user sets to the retailer, to enable the retailer to provide advertising for the one or more products to the multiple users of the selected one or more user sets, the electronic communicating of the selected one or more user sets being performed by the configured computer system.