1. A method for identifying consumer items more likely to be bought by a user, comprising: determining, by a computer having a processor and a memory, for each individual item of a plurality of items, a probability that the user will select the individual item, given that the user has expressed interest in a baseline item, wherein the probability is determined based on: a similarity among the plurality of items based on observable features thereof; an aggregate online search behavior across multiple users; and preferences of the user with respect to the baseline item, wherein the baseline item is established by the user; and ranking, in decreasing order, probabilities determined for the plurality of items, wherein items that are more likely to be bought by the user are ranked higher than items that are less likely to be bought by the user.