The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Nov. 04, 2014

Filed:

Feb. 27, 2012
Applicants:

Cedric Archambeau, Grenoble, FR;

Guillaume Bouchard, Crolles, FR;

Balaji Lakshminarayanan, London, GB;

Inventors:

Cedric Archambeau, Grenoble, FR;

Guillaume Bouchard, Crolles, FR;

Balaji Lakshminarayanan, London, GB;

Assignee:

Xerox Corporation, Norwalk, CT (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 15/18 (2006.01); G06N 99/00 (2010.01); G06N 3/08 (2006.01); G06K 9/62 (2006.01);
U.S. Cl.
CPC ...
G06N 99/005 (2013.01); G06K 9/6256 (2013.01); G06N 3/08 (2013.01);
Abstract

In a recommender method, Bayesian Matrix Factorization (BMF) is performed on a matrix having user and item dimensions and matrix elements containing user ratings for items made by users in order to train a probabilistic collaborative filtering model. A recommendation is generated for a user using the probabilistic collaborative filtering model. The recommendation may comprise a predicted item rating, or an identification of one or more recommended items. The recommender method is suitably performed by an electronic data processing device. The BMF may employ non-Gaussian priors, such as Student-t priors. The BMF may additionally or alternatively employ a heteroscedastic noise model comprising priors that include (1) a row dependent variance component that depends upon the matrix row and (2) a column dependent variance component that depends upon the matrix column.


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