1. A computer-implemented method of matching users to other users, the method comprising: storing, in computer storage, event data comprising order data reflective of items ordered from an electronic catalog by each of a plurality of users; programmatically generating a score that reflects a degree to which item preferences of a first user of said plurality of users are similar to item preferences of a second user of said plurality of users, said score taking into consideration a first plurality of items ordered by the first user and a second plurality of items ordered by the second user, wherein generating the score comprises weighting a first item and a second item identified in both the first and second plurality of items, wherein the first and second items are different, wherein the first and second items are weighted differently based at least in part on a first inherent characteristic of the first item and a second inherent characteristic of the second item, wherein the first and second inherent characteristics are different, and wherein generating the score further comprises taking into consideration at least one additional type of event data reflective of user affinities for items represented in the electronic catalog; and based at least in part on the score, programmatically determining whether to recommend the second user to the first user.
1. A computer-implemented method of matching users to other users, the method comprising: storing, in computer storage, event data comprising order data reflective of items ordered from an electronic catalog by each of a plurality of users; programmatically generating a score that reflects a degree to which item preferences of a first user of said plurality of users are similar to item preferences of a second user of said plurality of users, said score taking into consideration a first plurality of items ordered by the first user and a second plurality of items ordered by the second user, wherein generating the score comprises weighting a first item and a second item identified in both the first and second plurality of items, wherein the first and second items are different, wherein the first and second items are weighted differently based at least in part on a first inherent characteristic of the first item and a second inherent characteristic of the second item, wherein the first and second inherent characteristics are different, and wherein generating the score further comprises taking into consideration at least one additional type of event data reflective of user affinities for items represented in the electronic catalog; and based at least in part on the score, programmatically determining whether to recommend the second user to the first user. 4. The method of claim 1 , wherein generating the score further comprises accessing item similarity data to determine whether an item ordered by the first user is similar to an item ordered by the second user.