公开(公告)号：US20240086466A1

公开(公告)日：2024-03-14

申请号：US17943526

申请日：2022-09-13

Applicant: ROKU, INC.

Inventor： FEI XIAO ,  RONICA JETHWA ,  ZIDONG WANG ,  JING LU ,  JING YE ,  NAM VO ,  JOSE SANCHEZ ,  ABHISHEK BAMBHA ,  KHALDUN AIDARABSAH

IPC: G06F16/906

CPC classification number: G06F16/906

Abstract: Disclosed herein are various embodiments, for a content display and clustering system. An example embodiment operates by receiving a request to display the plurality of content items. At each of multiple levels different pairs of content items are identified and a similarity score is computed for each pair. A subset of pairs for which their similarity score exceeds a similarity threshold for the respective level are identified and clustered. This process is repeated for one or more iterations at the same level, and then the process is repeated for each of the multiple levels. A final clustered subset is identified, and output for display, responsive to the request to display the plurality of content items.

公开(公告)号：US20240214619A1

公开(公告)日：2024-06-27

申请号：US18089343

申请日：2022-12-27

Applicant: ROKU, INC.

Inventor： FEI XIAO ,  RONICA JETHWA ,  JING YE ,  ABHISHEK BAMBHA ,  ZIDONG WANG ,  JOSE SANCHEZ ,  NAM VO ,  KHALDUN AIDARABSAH ,  PULKIT AGGARWAL ,  LIAN LIU ,  ANIRBAN DAS ,  ROHIT MAHTO

IPC: H04N21/25 ,  H04N21/24 ,  H04N21/472

CPC classification number: H04N21/252 ,  H04N21/2407 ,  H04N21/472

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.