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. 20, 2019

Filed:

Nov. 21, 2016
Applicant:

Roku, Inc., Los Gatos, CA (US);

Inventor:

Sylvain René Yves Louboutin, Sunnyvale, CA (US);

Assignee:

ROKU, INC., Los Gatos, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H04N 21/25 (2011.01); H04L 12/26 (2006.01); H04L 29/08 (2006.01); H04N 21/442 (2011.01); H04N 21/45 (2011.01); H04N 21/466 (2011.01); H04N 21/81 (2011.01); G06F 11/34 (2006.01); G06Q 30/02 (2012.01);
U.S. Cl.
CPC ...
H04N 21/251 (2013.01); G06F 11/3438 (2013.01); G06Q 30/0201 (2013.01); H04L 43/045 (2013.01); H04L 67/22 (2013.01); H04N 21/44213 (2013.01); H04N 21/4532 (2013.01); H04N 21/4667 (2013.01); H04N 21/4668 (2013.01); H04N 21/812 (2013.01);
Abstract

Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for grouping users into user clusters based on common behavior patterns, and then recommending content to the users based on their respective membership in the clusters. Some embodiments operate by receiving tracking data for a user, where the tracking data includes content viewing behavior information of the user, and/or user interface (UI) navigation behavior information of the user. A distance between the tracking data and a cluster profile associated with a user cluster is determined. If the distance satisfies a threshold associated with the user cluster, then the user is added to the user cluster. Thereafter, the user's view experience is customized based the user's membership in the user cluster. For example, content recommendations may be generated for the user based on content previously provided to other users in the user cluster, where such content may or may not have previously been provided to the user.


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