1. A method of recommending items to users from a database of items, the method comprising: providing a table that maps items from the database to respective sets of similar items, wherein the table includes values that indicate degrees of similarity between specific items, said values reflecting an automated analysis of historical data indicating item interests of each of a plurality of users; and using the table to provide personalized item recommendations to each of a plurality of target users, wherein the personalized item recommendations are generated for a target user by at least: identifying multiple items selected by the target user; and selecting similar items from the table to recommend to the target user such that a determination of whether to recommend a particular similar item takes into consideration a degree to which that similar item is similar to each of the multiple items selected by the target user, as indicated by the table.