1. A system for using probabilistically-generated item associations to provide personalized item recommendations, the system comprising: a computer system comprising one or more processors, the computer system comprising: a probabilistic analysis component executed by the one or more processors, the probabilistic analysis component configured to: access item data from a data repository, the item data comprising information regarding a plurality of items, the data repository comprising physical computer storage; access user data comprising information about item selections by a plurality of users; programmatically generate an association between a first item and a second item of the item data based at least in part on the user data by at least: determining, from the user data, a first probability that first users selected both the first and second items, estimating, from the user data, a second probability that second users who selected the first item would have selected the second item independent of selecting the first item, said estimating comprising 1) determining a number of item selections other than the selection of the first item made by each of the second users and 2) using the number of item selections to estimate a probability that one of the other item selections was the second item, and deriving an association score for the first and second items based at least in part on a difference between the first probability and the second probability, the association score reflecting a value of the association between the first and second items; and a recommendation module executed by the one or more processors, the recommendation module configured to use the association to generate one or more item recommendations for a target user.