Patents by Inventor Abhishek Bambha
Abhishek Bambha has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 12389055Abstract: 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.Type: GrantFiled: December 27, 2022Date of Patent: August 12, 2025Assignee: Roku, Inc.Inventors: Fei Xiao, Ronica Jethwa, Jing Ye, Abhishek Bambha, Zidong Wang, Jose Sanchez, Nam Vo, Khaldun Aidarabsah, Pulkit Aggarwal, Lian Liu, Anirban Das, Rohit Mahto
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Publication number: 20250209815Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for deep video understanding with large language models. An example embodiment operates by determining a relationship between respective first and second visual elements for each of a plurality of frames of a content item based on respective element types and respective locations for the respective first and second visual elements. For each of the plurality of frames, a respective visual prompt is generated describing the relationship between the respective first and second visual elements. Based on an audio-to-text conversion of audio content associated with the frame or classification of aural elements of the audio content, a respective audio prompt describing the audio content associated with each frame is generated.Type: ApplicationFiled: December 21, 2023Publication date: June 26, 2025Applicant: Roku, Inc.Inventors: Fei XIAO, Abhishek BAMBHA, Rohit MAHTO, Nam VO, Ronica JETHWA, Atishay JAIN, Jose SANCHEZ, Lian LIU, Pulkit AGGARWAL, Amit VERMA, Zidong WANG
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Publication number: 20250209817Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product aspects, and/or combinations and sub-combinations thereof, for generating short-form content. An example aspect operates by analyzing a media file in a library using a machine learning model. To analyze the media file, the embodiment determines, using the machine learning model, a first portion of the media file that has a feature that satisfies a classification that the machine learning model is configured to identify. The embodiment tags the first portion using one or more position tags indicative of a beginning of the first portion of the media file or an end of the first portion of the media file. The embodiment then generates a segment from the media file based on the one or more position tags. The segment comprises the portion of the media file and excludes one or more second portions of the media file.Type: ApplicationFiled: December 22, 2023Publication date: June 26, 2025Applicant: Roku, Inc.Inventors: Fei XIAO, Nam VO, Ronica JETHWA, Abhishek BAMBHA, Rohit MAHTO, Amit VERMA, Pulkit AGGARWAL, Zidong WANG
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Publication number: 20250208885Abstract: Disclosed herein are system, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for personalizing a user interface (UI) of a media device and/or content presented thereby. An example embodiment operates by obtaining a first natural language user input, providing the first natural language user input to a personalization language model that is configured to interpret different natural language user inputs to respectively determine different update tasks invoked thereby, the different update tasks including a UI update task and a content update task, receiving from the model a first update task determined thereby based at least on the first natural language user input, generating one or more first application programming interface (API) calls based on the first update task, and placing the one or more first API calls to a service that implements the first update task based on the one or more first API calls.Type: ApplicationFiled: March 10, 2025Publication date: June 26, 2025Applicant: ROKU, INC.Inventors: Atishay Jain, Fei Xiao, Abhishek Bambha, Mehul Agrawal, Rohit Mahto
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Publication number: 20250184571Abstract: Disclosed herein are system, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for recommending content items. For example, a first content item unassociated with interaction-based data is determined. A description-based representation of the first content item, an image-based representation of the first content item, and/or a metadata-based representation of the first content item is obtained from machine learning model(s). Such representation(s) are provided as an input to a neural network. A first interaction-based representation of the first content item based on such representation(s) is received as an output from the neural network. A measure of similarity is determined between the first interaction-based representation and second interaction-based representation(s) of second content item(s).Type: ApplicationFiled: November 30, 2023Publication date: June 5, 2025Inventors: PULKIT AGGARWAL, FEI XIAO, ABHISHEK BAMBHA, ROHIT MAHTO, RAMEEN MAHDAVI, NAM VO, AMIT VERMA
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Publication number: 20250173378Abstract: 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.Type: ApplicationFiled: January 6, 2025Publication date: May 29, 2025Applicant: ROKU, INC.Inventors: Fei XIAO, Ronica JETHWA, Zidong WANG, Jing LU, Jing YE, Nam VO, Jose SANCHEZ, Abhishek BAMBHA, Khaldun AIDARABSAH
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Patent number: 12301897Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for generating a scene emotion value for a scene based on a sequence of frame emotion values for a sequence of frames within the scene of a content. The content can include multiple scenes, and a scene can include multiple frames, where a frame emotion value can be generated for each frame. A frame emotion value can be generated based on scene metadata related to the scene, content metadata related to the content, and a frame metadata related to the frame.Type: GrantFiled: January 29, 2024Date of Patent: May 13, 2025Assignee: Roku, Inc.Inventors: Ronica Jethwa, Nam Vo, Fei Xiao, Abhishek Bambha
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Publication number: 20250133251Abstract: 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.Type: ApplicationFiled: December 19, 2024Publication date: April 24, 2025Applicant: ROKU, INC.Inventors: Fei XIAO, Zidong WANG, Jose SANCHEZ, Abhishek BAMBHA, Ronica JETHWA
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Patent number: 12282784Abstract: Disclosed herein are system, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for personalizing a user interface (UI) of a media device and/or content presented thereby. An example embodiment operates by obtaining a first natural language user input, providing the first natural language user input to a personalization language model that is configured to interpret different natural language user inputs to respectively determine different update tasks invoked thereby, the different update tasks including a UI update task and a content update task, receiving from the model a first update task determined thereby based at least on the first natural language user input, generating one or more first application programming interface (API) calls based on the first update task, and placing the one or more first API calls to a service that implements the first update task based on the one or more first API calls.Type: GrantFiled: October 13, 2023Date of Patent: April 22, 2025Assignee: ROKU, INC.Inventors: Atishay Jain, Fei Xiao, Abhishek Bambha, Mehul Agrawal, Rohit Mahto
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Publication number: 20250124468Abstract: An example method of message routing includes: receiving, by one or more processors, a request to send a message to a specified user of a plurality of users of a communication services platform; providing a user profile of the specified user to a communication channel selection model, wherein the user profile characterizes actions of one or more predefined action types that were performed by the specified user in response to receiving previous communications; identifying, based on the output of the communication channel selection model, a preferred communication channel for communicating with the specified user; determining, based on the preferred communication channel, a communication strategy for the specified user; and causing, pursuant to the communication strategy, a message to be sent to the specified user.Type: ApplicationFiled: December 17, 2024Publication date: April 17, 2025Inventors: Claire Electra Longo, Brendon Kyle Villalobos, Liyuan Zhang, Jorge Chang, Elizabeth Yee, Abhishek Bambha
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Publication number: 20250123857Abstract: Disclosed herein are system, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for personalizing a user interface (UI) of a media device and/or content presented thereby. An example embodiment operates by obtaining a first natural language user input, providing the first natural language user input to a personalization language model that is configured to interpret different natural language user inputs to respectively determine different update tasks invoked thereby, the different update tasks including a UI update task and a content update task, receiving from the model a first update task determined thereby based at least on the first natural language user input, generating one or more first application programming interface (API) calls based on the first update task, and placing the one or more first API calls to a service that implements the first update task based on the one or more first API calls.Type: ApplicationFiled: October 13, 2023Publication date: April 17, 2025Applicant: ROKU, INC.Inventors: Atishay Jain, Fei Xiao, Abhishek Bambha, Mehul Agrawal, Rohit Mahto
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Publication number: 20250117825Abstract: An example method of message routing includes: receiving a request to send a message to a specified user of a plurality of users of a communication services platform; providing a user profile of the specified user to a send time optimization model, wherein the user profile characterizes actions of one or more predefined action types that were performed by the specified user in response to receiving previous communications; identifying, based on the output of the send time optimization model, a preferred time range for communicating with the specified user; and causing, within the preferred time range, a message to be sent to the specified user.Type: ApplicationFiled: December 17, 2024Publication date: April 10, 2025Inventors: Claire Electra Longo, Brendon Kyle Villalobos, Liyuan Zhang, Jorge Chang, Elizabeth Yee, Abhishek Bambha
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Patent number: 12235905Abstract: 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.Type: GrantFiled: February 7, 2024Date of Patent: February 25, 2025Assignee: Roku, Inc.Inventors: Fei Xiao, Ronica Jethwa, Zidong Wang, Jing Lu, Jing Ye, Nam Vo, Jose Sanchez, Abhishek Bambha, Khaldun Aidarabsah
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Publication number: 20250053853Abstract: Disclosed are system, method and/or computer program product embodiments for improving the performance of a machine learning based algorithm used to provide a user experience to a user via a media device. An embodiment selects a first set of hyperparameter values, implements a first iteration of the algorithm based on the first set of hyperparameter values, utilizes the first iteration of the algorithm to provide a first user experience to the user, determines a response of the user to the first user experience, selects, by a hyperparameter tuning ML model implemented as a contextual multi-arm bandit model or a reinforcement learning model and based on at least the response of the user, a second set of hyperparameter values, implements a second iteration of the algorithm based on the second set of hyperparameter values, and utilizes the second iteration of the algorithm to provide a second user experience to the user.Type: ApplicationFiled: August 10, 2023Publication date: February 13, 2025Inventors: FEI XIAO, ZIDONG WANG, LIAN LIU, NAM VO, WEICONG DING, ABHISHEK BAMBHA, AMIT VERMA, AASISH SIPANI, ROHIT MAHTO, HOSSEIN DABIRIAN, JOSE SANCHEZ
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Publication number: 20250047917Abstract: 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.Type: ApplicationFiled: October 22, 2024Publication date: February 6, 2025Applicant: ROKU, INC.Inventors: Pulkit AGGARWAL, Abhishek BAMBHA, Rohit MAHTO, Nam VO, Fei XIAO
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Patent number: 12219190Abstract: 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.Type: GrantFiled: August 18, 2022Date of Patent: February 4, 2025Assignee: Roku, Inc.Inventors: Fei Xiao, Zidong Wang, Jose Sanchez, Abhishek Bambha, Ronica Jethwa
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Publication number: 20250024123Abstract: 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.Type: ApplicationFiled: September 25, 2024Publication date: January 16, 2025Applicant: ROKU, INC.Inventors: Abhishek BAMBHA, RONICA JETHWA, ROHIT MAHTO, NAM VO, FEI XIAO, LIAN LIU
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Publication number: 20250016425Abstract: 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.Type: ApplicationFiled: September 10, 2024Publication date: January 9, 2025Applicant: ROKU, INC.Inventors: Fei XIAO, Abhishek Bambha, Nam Vo, Pulkit Aggarwal, Rohit Mahto, Andrey Vlasenko, Rameen Mahdavi
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Patent number: 12190864Abstract: Disclosed herein are system, method and/or computer program product embodiments, and/or combinations thereof, for training a conversational recommendation system. An embodiment generates a probabilistic pseudo-user neural network model based on at least one interest probability distribution corresponding to a pseudo-user profile. The embodiment trains, using the pseudo-user neural network model, the conversational recommendation system to learn a recommendation policy, where the conversational recommendation system includes an interest-exploration engine and a prompt-decision engine. The training includes performing an iterative learning process that includes selecting an interest-exploration strategy based on one or more of the following: an interest-exploration policy, an earlier pseudo-user response generated by the pseudo-user neural network model, content data, and pseudo-user interaction history.Type: GrantFiled: June 5, 2024Date of Patent: January 7, 2025Assignee: Roku, Inc.Inventors: Fei Xiao, Amit Verma, Rohit Mahto, Rameen Mahdavi, Nam Vo, Zidong Wang, Lian Liu, Jose Sanchez, Pulkit Aggarwal, Atishay Jain, Abhishek Bambha, Ronica Jethwa
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Publication number: 20240412271Abstract: 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.Type: ApplicationFiled: June 12, 2023Publication date: December 12, 2024Inventors: Fei XIAO, Lian LIU, Jose SANCHEZ, Nam VO, Atishay JAIN, Ronica JETHWA, Pulkit AGGARWAL, Rohit MAHTO, Abhishek BAMBHA, Amit VERMA, Daniel MEROPOL, Rameen MAHDAVI