METHODS AND SYSTEMS FOR GENERATING RECOMMENDATION LIST WITH DIVERSITY

摘要

Systems and methods for automatically generating a user-specific recommendation list with diversified as well as relevant items. Recommendation categories and sample items for each category are diversified by virtue of probability distribution. Items in a user' collection can be clustered based on category in accordance with a similarity measure. The category probability distribution values may be derived from characteristics suggesting respective categories' importance or preference to the user. For each selected category, the sample probability distribution values may be derived from similarities of each candidate to the selected category.

主权项

1. A computer implemented method of automatically generating a recommendation list of commodities to a user, said method comprising:
accessing a user inventory comprising a collection of commodities in a plurality of categories of commodities; partitioning said collection of commodities into a plurality of clusters of commodities, each cluster corresponding to a respective category of said plurality of categories; assigning respective probability distribution values to said plurality of categories; determining a selection set of categories from said plurality of categories for a recommendation instance based on probability distribution values of said plurality categories; determining a respective sample commodity for each category of said selection set of categories to produce a plurality of sample recommendations, wherein said plurality of sample recommendations are selected from a stock of commodities; and presenting said recommendation list identifying said plurality of sample commodities for said selection set of categories.