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:
Sep. 18, 2018

Filed:

May. 12, 2017
Applicant:

Google Inc., Mountain View, CA (US);

Inventors:

Ullas Gargi, Los Altos, CA (US);

Jay N. Yagnik, Mountain View, CA (US);

Anindya Sarkar, Goleta, CA (US);

Assignee:

GOOGLE LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04N 7/16 (2011.01); H04H 60/32 (2008.01); H04N 21/234 (2011.01); H04N 21/237 (2011.01); H04N 21/25 (2011.01); H04N 21/258 (2011.01); H04N 21/466 (2011.01);
U.S. Cl.
CPC ...
H04N 21/23418 (2013.01); H04N 21/237 (2013.01); H04N 21/251 (2013.01); H04N 21/25891 (2013.01); H04N 21/466 (2013.01);
Abstract

User engagement in unwatched videos is predicted by collecting and aggregating data describing user engagement with watched videos. The data are normalized to reduce the influence of factors other than the content of the videos on user engagement. Engagement metrics are calculated for segments of watched videos that indicate user engagement with each segment relative to overall user engagement with the watched videos. Features of the watched videos within time windows are characterized, and a function is learned that relates the features of the videos within the time windows to the engagement metrics for the time windows. The features of a time window of an unwatched video are characterized, and the learned function is applied to the features to predict user engagement to the time window of the unwatched video. The unwatched video can be enhanced based on the predicted user engagement.


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