SYSTEM, METHOD AND COMPUTER PROGRAM PRODUCT FOR PREDICTING ITEM PREFERENCE USING REVENUE-WEIGHTED COLLABORATIVE FILTER

摘要

Embodiments disclosed provide a system, method, and computer program product for identifying consumer items more likely to be bought by an individual user. In some embodiments, a collaborative filter may be used to rank items based on the degree to which they match user preferences. The collaborative filter may be hierarchical and may take various factors into consideration. Example factors may include the similarity among items based on observable features, a summary of aggregate online search behavior across multiple users, the item features determined to be most important to the individual user, and a baseline item against which a conditional probability of another item being selected is measured.

主权项

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; andpreferences 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.