1. A computer-implemented method, comprising: retrieving item preference data for a target user from computer storage, said item preference data reflective of item preferences of the target user; generating a recommendation set using the retrieved item preference data, said recommendation set comprising a computer representation of items predicted to be of interest to the target user; filtering the recommendation set, wherein filtering the recommendation set comprises filtering out a first item from the recommendation set based at least partly on a determination that the first item has at least a threshold degree of similarity to a second item in the recommendation set, said first and second items not being duplicates of each other, said filtering producing a filtered recommendation set that has a higher degree of item diversity than the recommendation set; and outputting at least a portion of the the filtered recommendation set for presentation to the target user; said method performed by a computer system that comprises one or more computers.