公开(公告)号：US20250024123A1

公开(公告)日：2025-01-16

申请号：US18895850

申请日：2024-09-25

Applicant: ROKU, INC.

Inventor： Abhishek BAMBHA ,  RONICA JETHWA ,  ROHIT MAHTO ,  NAM VO ,  FEI XIAO ,  LIAN LIU

IPC: H04N21/8549 ,  G06F16/783

Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product aspects, and/or combinations and sub-combinations thereof, for generating trailers (previews) for multimedia content. An example aspect operates by generating an initial set of candidate points to generate a trailer for a media content; determining conversion data for each of the initial set of candidate points; determining an updated set of candidate points based on the conversion data; determining an estimated mean and upper bound for each of the updated set of candidate points; computing a value for each of the updated set of candidate points; generating a ranked list based on the value computed for each of the updated set of candidate points; and repeating the process until an optimal candidate point is converged upon.

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：US20250133251A1

公开(公告)日：2025-04-24

申请号：US18988182

申请日：2024-12-19

Applicant: ROKU, INC.

Inventor： Fei XIAO ,  Zidong WANG ,  Jose SANCHEZ ,  Abhishek BAMBHA ,  Ronica JETHWA

IPC: H04N21/25 ,  H04N21/258

Abstract: Disclosed are mechanisms for selecting a recommended item for a current item being viewed by a user account based on a view history of the user account with reduced bias. For a current item being viewed by the user account represented by a current node of a co-watch graph, embodiments can select a recommended item represented by an associated node in the co-watch graph likely being viewed by the user account, and determine a probability of the recommended item likely being viewed. The co-watch graph can be generated based on a view history of the user account. An edge between a first node and a second node of the co-watch graph can have a weight representing a number of co-occurrence times when the first item represented by the first node and the second item represented by the second node are viewed in sequence within a predetermined time interval.

公开(公告)号：US20240127106A1

公开(公告)日：2024-04-18

申请号：US17965284

申请日：2022-10-13

Applicant: Roku, Inc.

Inventor： Abhishek BAMBHA ,  Weicong DING ,  Zidong WANG ,  Fei XIAO

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for online automatic hyperparameter tuning of a machine learning model that provides a user experience to media devices such that the machine learning model maximizes (or minimizes) an objective function. An example embodiment operates by generating an initial set of hyperparameter configurations for a machine learning model based on sampling data received from media devices over a network. The embodiment then determines, using an hyperparameter tuning method, a hyperparameter configuration based on the initial set of hyperparameter configurations that causes a training of the machine learning model using a learning algorithm to maximize an objective function. The embodiment then trains the machine learning model according to the determined hyperparameter configuration using the learning algorithm. The embodiment then provides, using the trained machine learning model, a user experience to the media devices.

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.

公开(公告)号：US20240112041A1

公开(公告)日：2024-04-04

申请号：US17937497

申请日：2022-10-03

Applicant: ROKU, INC

Inventor： Abhishek BAMBHA ,  Rohit MAHTO ,  Nam VO ,  Zidong WANG ,  Fei XIAO

IPC: G06N5/02 ,  G06N5/04

CPC classification number: G06N5/02 ,  G06N5/048

Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for stochastic candidate selection for content recommendation. An example embodiment operates by a computer-implemented method for stochastic candidate selection for content recommendation. The method includes receiving, by at least one computer processor, a first plurality of content candidates and selecting a second plurality of content candidates from the first plurality of content candidates. The method further include ranking the second plurality of content candidates based on one or more parameters and selecting a third plurality of content candidates from the ranked second plurality of content candidates. The method can further include displaying the third plurality of content candidates using a display device.