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:
Feb. 16, 2016

Filed:

Dec. 01, 2014
Applicant:

Linkedin Corporation, Mountain View, CA (US);

Inventors:

Jonathan David Traupman, Oakland, CA (US);

Deepak Agarwal, Sunnyvale, CA (US);

Liang Zhang, Fremont, CA (US);

Bo Long, Palo Alto, CA (US);

Frank Emmanuel Astier, Mountain View, CA (US);

Assignee:

LinkedIn Corporation, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 5/02 (2006.01); G06Q 50/00 (2012.01); H04L 12/58 (2006.01); G06F 17/30 (2006.01); G06N 5/04 (2006.01); G06N 7/00 (2006.01); G06N 99/00 (2010.01);
U.S. Cl.
CPC ...
G06N 5/02 (2013.01); G06F 17/30286 (2013.01); G06N 5/048 (2013.01); G06N 7/005 (2013.01); G06N 99/005 (2013.01); G06Q 50/01 (2013.01); H04L 51/00 (2013.01); H04L 51/32 (2013.01);
Abstract

Techniques for predicting a user response to content are provided. In example embodiments, one or more feature vectors are assembled into an assembled feature vector. A particular one of the feature vectors not being available is determined. In response to determining that the particular one of the feature vectors is not available, the particular feature vector is ignored based on an importance value associated with the particular feature vector. A substitute value associated with the particular feature vector is inserted into a portion of the assembled feature vector associated with the particular feature vector. A prediction modeling process based on the assembled feature vector and a prediction model is performed to predict a likelihood of a particular member performing a particular user action on a particular content item.


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