公开(公告)号：US20240223869A1

公开(公告)日：2024-07-04

申请号：US18091234

申请日：2022-12-29

Applicant: ROKU, INC.

Inventor： Fei XIAO ,  Abhishek BAMBHA ,  Nam VO ,  Pulkit AGGARWAL ,  Rohit MAHTO ,  Andrey VLASENKO ,  Rameen MAHDAVI

IPC: H04N21/81 ,  G06Q30/0241 ,  G06Q30/0251 ,  H04N21/25 ,  H04N21/254

CPC classification number: H04N21/812 ,  G06Q30/0249 ,  G06Q30/0254 ,  H04N21/251 ,  H04N21/2542

Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for a content acquisition system to recommend for acquisition a subset of content items selected from a set of content items available for purchase in relation to a content recommendation system currently used in a media environment. The content acquisition system may include a content recommendation system simulator to estimate an impact function value for a potential subset of content items of the set of content items available for purchase based on the currently used content recommendation system. Afterwards, an acquisition recommender can recommend for acquisition a subset of content items based on an optimized objective function value calculated based on an optimization model while meeting one or more budget constraints.

公开(公告)号：US20240412271A1

公开(公告)日：2024-12-12

申请号：US18208717

申请日：2023-06-12

Applicant: ROKU, INC.

Inventor： Fei XIAO ,  Lian LIU ,  Jose SANCHEZ ,  Nam VO ,  Atishay JAIN ,  Ronica JETHWA ,  Pulkit AGGARWAL ,  Rohit MAHTO ,  Abhishek BAMBHA ,  Amit VERMA ,  Daniel MEROPOL ,  Rameen MAHDAVI

IPC: G06Q30/0601

Abstract: Disclosed herein are system, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for recommending content to a user. An embodiment identifies a first set of content items based at least on a first set of weights respectively associated with different user interests, causes the first set of content items to be presented to the user, determines a measure of user interaction with the first set of content items, provides the measure of user interaction to one of a multi-arm bandit (MAB), contextual MAB, or reinforcement learning model that selects, based at least on the state information and the measure of user interaction, a second set of weights respectively associated with the different user interests, identifies a second set of content items based at least on the second set of weights, and causes the second set of content items to be presented to the user.

公开(公告)号：US20250047917A1

公开(公告)日：2025-02-06

申请号：US18922892

申请日：2024-10-22

Applicant: ROKU, INC.

Inventor： Pulkit AGGARWAL ,  Abhishek BAMBHA ,  Rohit MAHTO ,  Nam VO ,  Fei XIAO

IPC: H04N21/25 ,  H04N21/258

Abstract: Disclosed herein are system, apparatus, article of manufacture, method, and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for demographic predictions for content items. An example embodiment operates by assigning weights representing demographics to a first plurality of nodes of a predictive model and assigning predictive values representing predicted demographics to a second plurality of nodes of the model. Pairwise distances between the predictive values for the nodes of the second plurality of nodes and the weighted values of the first plurality of nodes may be calculated and the shortest calculated pairwise distances may be used to assign demographics for content items corresponding to nodes of the first plurality of nodes to content items corresponding nodes of the second plurality of nodes. When content is requested, a content item for which the same demographic has been assigned may be recommended to the requestor.