1. A computer-implemented method of generating personalized recommendations of items, the method comprising: maintaining an item collection of a user in computer storage, said item collection being a computer representation of a plurality of items selected by the user from an electronic catalog of items; applying a clustering algorithm to the item collection to subdivide the collection into multiple clusters of items, said clusters generated based, at least in part, on calculated distances between the items; outputting a visual representation of the multiple clusters for presentation to the user via a user interface that enables the user to rate specific clusters of items, said visual representation enabling the user to identify particular items included in each of said clusters; receiving an indication of a cluster rating specified by the user via said user interface, said cluster rating corresponding to a cluster selected by the user from said visual representation, and representing a collective rating by said user of multiple items in said cluster; generating personalized item recommendations for the user based in part on the cluster rating, wherein generating the personalized recommendations comprises using the cluster rating as a default rating of items that the user has not individually rated in the cluster, and comprises using said default ratings of individual items, in combination with non-default ratings explicitly assigned by the user to particular items, to select additional items to recommend to the user; and outputting a representation of the personalized item recommendations for presentation to the user; said method performed by a computer system that comprises one or more computing devices.