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, wherein the items are represented in a hierarchical browse structure of said electronic catalog, said hierarchical browse structure comprising multiple levels of browse nodes; applying a clustering algorithm to the item collection to subdivide the collection into multiple clusters of said items, said clusters generated based, at least in part, on calculated distances between the items in the hierarchical browse structure, said distances being dependent upon the browse nodes to which particular items are assigned; 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 by execution of code modules by a computer system, wherein generating the personalized item recommendations comprises taking the cluster rating into consideration in selecting items from the item collection to use as recommendation sources, and by identifying, for recommendation to the user, additional items that are related to said recommendation source items, such that the personalized item recommendations are based on a selected subset of the item collection; and outputting a representation of the personalized item recommendations for presentation to the user.