1. A computerized method comprising: accessing at least one data store that provides information regarding prior ad presentation opportunities and information regarding actions taken by users in response to the prior ad presentation opportunities; providing at least one ad opportunity signature to a plurality of different content providers; receiving ad candidates from the plurality of different content providers at least partly in response to providing the at least one ad opportunity signature; generating a model based on information accessed from said at least one data store using a machine learning approach, wherein the model maps ad presentation opportunities to ad candidates received from the plurality of different content providers that are assessed as appropriate for the respective ad presentation opportunities; using the model to map a new ad presentation opportunity to one or more ad candidates; and filtering the one or more ad candidates, wherein the filtering comprises reducing or eliminating ad selections which do not exhibit a preferred degree of variation.