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:
Aug. 07, 2018

Filed:

Oct. 30, 2015
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Mohammad Shafkat Amin, Cupertino, CA (US);

Baoshi Yan, Belmont, CA (US);

Craig Martell, San Juan Bautista, CA (US);

Vita Markman, San Francisco, CA (US);

Anmol Bhasin, Los Altos, CA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 17/00 (2006.01); G06F 17/28 (2006.01); G10L 15/00 (2013.01); H04L 12/58 (2006.01); G06F 17/27 (2006.01); G06Q 50/00 (2012.01);
U.S. Cl.
CPC ...
G06F 17/289 (2013.01); G06F 17/27 (2013.01); G06F 17/2854 (2013.01); G06Q 50/01 (2013.01); H04L 51/12 (2013.01);
Abstract

This disclosure provides systems and methods for determining a classification model for a secondary language different from a primary language. A social networking server is configured to obtain primary language content written in a first spoken language and secondary language content written in a second spoken language. The social networking server further obtains a machine translation of the primary language content. The social networking server then determines an initial language model from the machine translation. The social networking further determines a language model perturbation using the initial language model, where the language model perturbation accounts for a difference between the machine translation and the secondary language content. The social networking server also determines a classification model from the initial language model and the language model perturbation, which is then applied to a plurality of comments associated with an item of interest provided by a social networking service.


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