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. 12, 2013

Filed:

Jun. 18, 2010
Applicants:

Elena Zheleva, College Park, MD (US);

John Guiver, Saffron Walden, GB;

Natasa Milic-frayling, Cambridge, GB;

Eduarda Mendes Rodrigues, Vila Nova de Gaia, PT;

Inventors:

Elena Zheleva, College Park, MD (US);

John Guiver, Saffron Walden, GB;

Natasa Milic-Frayling, Cambridge, GB;

Eduarda Mendes Rodrigues, Vila Nova de Gaia, PT;

Assignee:

Microsoft Corporation, Redmond, WA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 7/00 (2006.01); G06F 17/30 (2006.01);
U.S. Cl.
CPC ...
Abstract

Recommending a media item may include, for example, a statistical model of media consumption is applied to media session consumption data from a community of users to infer parameters of the model. The model comprises a first probability distribution for each user defining a likelihood of the user having a latent characteristic for a session, and a second probability distribution for each latent characteristic defining a likelihood of a user selecting a media item given the latent characteristic. In another example, the inferred parameters are provided to a recommendation engine arranged to recommend media items. The recommendation engine uses the model with inferred parameters and data describing media items newly consumed by a user to infer a current latent characteristic for a current session of the user, and uses them to generate recommended media items for the user in the current session based on the current latent characteristic.


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