3. The method of claim 1 , further comprising generating multiple distinct portions of the set of training images, wherein each of the multiple distinct portions is generated to include fewer than all of the images in the set of training images.
3. The method of claim 1 , further comprising generating multiple distinct portions of the set of training images, wherein each of the multiple distinct portions is generated to include fewer than all of the images in the set of training images. 4. The method of claim 3 , wherein generating a re-trained image relevance model comprises generating, for each distinct portion, based on content feature values of the distinct portion and the image selection data associated with the aggregation of near duplicate images included in the distinct portion.