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. 12, 2025

Filed:

Dec. 27, 2022
Applicant:

Roku, Inc., San Jose, CA (US);

Inventors:

Fei Xiao, San Jose, CA (US);

Ronica Jethwa, Mountain View, CA (US);

Jing Ye, San Jose, CA (US);

Abhishek Bambha, Burlimgame, CA (US);

Zidong Wang, San Jose, CA (US);

Jose Sanchez, San Jose, CA (US);

Nam Vo, San Jose, CA (US);

Khaldun Aidarabsah, San Jose, CA (US);

Pulkit Aggarwal, San Jose, CA (US);

Lian Liu, San Jose, CA (US);

Anirban Das, San Jose, CA (US);

Rohit Mahto, San Jose, CA (US);

Assignee:

Roku, Inc., San Jose, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04N 21/25 (2011.01); H04N 21/24 (2011.01); H04N 21/472 (2011.01);
U.S. Cl.
CPC ...
H04N 21/252 (2013.01); H04N 21/2407 (2013.01); H04N 21/472 (2013.01);
Abstract

A set of content items can be accessed by a community of users having a set of interests. A set of interest based clusters for the set of content items correspond to the set of interests. For a user, a recommendation system can determine a group of user interest clusters selected from the set of interest based clusters. A popularity score for each content item of the set of content items with respect to the community of users can be generated, and an interest based popularity score for a content item within the interest based cluster can be generated based on a rank of the content item based on the popularity score of the content item. Recommendation candidates for the user can be generated based on the interest based popularity score of the content item for each content item in the group of user interest clusters.


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