Patents by Inventor Nikhil Belsare
Nikhil Belsare 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: 11960517Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that generate a dynamic cross-platform ask interface and utilize a cross-platform language processing model to provide platform-specific, contextually based responses to natural language digital text queries. In particular, in one or more embodiments, the disclosed systems utilize machine learning models to extract registered intents from digital text queries to identify platform-specific configurations associated with the registered intents. Utilizing the platform-specific configurations, the disclosed systems can generate tailored platform-specific requests for information, as well as customized end-user search results that cause client devices to efficiently, accurately, and flexibly render platform-specific search results.Type: GrantFiled: July 22, 2021Date of Patent: April 16, 2024Assignee: Adobe Inc.Inventors: Piyush Gupta, Binit Kumar Sinha, Eunyee Koh, Fan Du, Gaurav Makkar, Silky Kedawat, Subrahmanya Kumar Giliyaru, Vasanthi Holtcamp, Nikhil Belsare
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Patent number: 11836172Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for facilitating data visualization generation. In one implementation, dataset intent data, visual design intent data, and insight intent data determined from a user input natural language query are obtained. A set of candidate intent recommendations is generated using various combinations of the dataset intent data, visual design intent data, and insight intent data. Each of the candidate intent recommendations is incorporated into a set of visualization templates to determine eligibility of the candidate intent recommendations. For eligible candidate intent recommendations, a score associated with a corresponding visualization template is determined. Based on the scores, a candidate intent recommendation and corresponding visualizations template is selected to use as a visual recommendation for presenting a data visualization.Type: GrantFiled: June 22, 2021Date of Patent: December 5, 2023Assignee: Adobe Inc.Inventors: Fan Du, Zening Qu, Vasanthi Swaminathan Holtcamp, Tak Yeon Lee, Sungchul Kim, Saurabh Mahapatra, Sana Malik Lee, Ryan A. Rossi, Nikhil Belsare, Eunyee Koh, Andrew Thomson, Sumit Shekhar
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Publication number: 20230030341Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that utilize a dynamic user interface and machine learning tools to generate data-driven digital content and multivariate testing recommendations for distributing digital content across computer networks. In particular, in one or more embodiments, the disclosed systems utilize machine learning models to generate digital recommendations at multiple development stages of digital communications that are targeted on particular performance metrics. For example, the disclosed systems utilize historical information and recipient profile data to generate recommendations for digital communication templates, fragment variants of content fragments, and content variants of digital content items.Type: ApplicationFiled: July 22, 2021Publication date: February 2, 2023Inventors: Eunyee Koh, Tak Yeon Lee, Andrew Thomson, Vasanthi Holtcamp, Ryan Rossi, Fan Du, Caroline Kim, Tong Yu, Shunan Guo, Nedim Lipka, Shriram Venkatesh Shet Revankar, Nikhil Belsare
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Publication number: 20230021797Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that generate a dynamic cross-platform ask interface and utilize a cross-platform language processing model to provide platform-specific, contextually based responses to natural language digital text queries. In particular, in one or more embodiments, the disclosed systems utilize machine learning models to extract registered intents from digital text queries to identify platform-specific configurations associated with the registered intents. Utilizing the platform-specific configurations, the disclosed systems can generate tailored platform-specific requests for information, as well as customized end-user search results that cause client devices to efficiently, accurately, and flexibly render platform-specific search results.Type: ApplicationFiled: July 22, 2021Publication date: January 26, 2023Inventors: Piyush Gupta, Binit Kumar Sinha, Eunyee Koh, Fan Du, Gaurav Makkar, Silky Kedawat, Subrahmanya Kumar Giliyaru, Vasanthi Holtcamp, Nikhil Belsare
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Publication number: 20220405314Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for facilitating data visualization generation. In one implementation, dataset intent data, visual design intent data, and insight intent data determined from a user input natural language query are obtained. A set of candidate intent recommendations is generated using various combinations of the dataset intent data, visual design intent data, and insight intent data. Each of the candidate intent recommendations is incorporated into a set of visualization templates to determine eligibility of the candidate intent recommendations. For eligible candidate intent recommendations, a score associated with a corresponding visualization template is determined. Based on the scores, a candidate intent recommendation and corresponding visualizations template is selected to use as a visual recommendation for presenting a data visualization.Type: ApplicationFiled: June 22, 2021Publication date: December 22, 2022Inventors: Fan Du, Zening Qu, Vasanthi Swaminathan Holtcamp, Tak Yeon Lee, Sungchul Kim, Saurabh Mahapatra, Sana Malik Lee, Ryan A. Rossi, Nikhil Belsare, Eunyee Koh, Andrew Thomson, Sumit Shekhar
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Publication number: 20220100714Abstract: Systems and methods for lifelong schema matching are described. The systems and methods include receiving data comprising a plurality of information categories, classifying each information category according to a schema comprising a plurality of classes, wherein the classification is performed by a neural network classifier trained based on a lifelong learning technique using a plurality of exemplar training sets, wherein each of the exemplar training sets includes a plurality of examples corresponding to one of the classes, and wherein the examples are selected based on a metric indicating how well each of the examples represents the corresponding class, and adding the data to a database based on the classification, wherein the database is organized according to the schema.Type: ApplicationFiled: September 29, 2020Publication date: March 31, 2022Inventors: Handong Zhao, Yikun Xian, Sungchul Kim, Tak Yeon Lee, Nikhil Belsare, Shashi Kant Rai, Vasanthi Holtcamp, Thomas Jacobs, Duy-Trung T. Dinh, Caroline Jiwon Kim
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Patent number: 10949873Abstract: Systems and methods are disclosed for enabling incremental reach for an advertising campaign, across multiple screens/channels. In some embodiments, a base TV/media plan is uploaded, and targeted exposed viewers are monitored. Unexposed target viewers are identified. Additional media channels that unexposed viewers use are found. Unexposed viewers are matched with pricing and media avails from one or more media directories. Media avails are then analyzed along with incremental on-target impressions. Targeted avails for unexposed viewers are then determined, based on lowest incremental cost and largest incremental reach are added to a current cross-screen plan. An analysis to find new unexposed viewers is then re-run to determine the next-most cost effective avails. The above steps are repeated or looped until a selected advertisement budget has been allocated. User interface embodiments for these methods are also disclosed.Type: GrantFiled: June 12, 2019Date of Patent: March 16, 2021Assignee: ADOBE INC.Inventors: Antoine Barbier, Greg Collison, Albert Lim, Nikhil Belsare, Alexander R. Hood
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Patent number: 10445766Abstract: Systems and methods are disclosed for enabling incremental reach for an advertising campaign, across multiple screens/channels. In some embodiments, a base TV/media plan is uploaded, and targeted exposed viewers are monitored. Unexposed target viewers are identified. Additional media channels that unexposed viewers use are found. Unexposed viewers are matched with pricing and media avails from one or more media directories. Media avails are then analyzed along with incremental on-target impressions. Targeted avails for unexposed viewers are then determined, based on lowest incremental cost and largest incremental reach are added to a current cross-screen plan. An analysis to find new unexposed viewers is then re-run to determine the next-most cost effective avails. The above steps are repeated or looped until a selected advertisement budget has been allocated. User interface embodiments for these methods are also disclosed.Type: GrantFiled: September 30, 2016Date of Patent: October 15, 2019Assignee: ADOBE INC.Inventors: Antoine Barbier, Greg Collison, Albert Lim, Nikhil Belsare, Alexander R. Hood
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Patent number: 10445765Abstract: Systems and methods are disclosed for enabling incremental reach for an advertising campaign, across multiple screens/channels. In some embodiments, a base TV/media plan is uploaded, and targeted exposed viewers are monitored. Unexposed target viewers are identified. Additional media channels that unexposed viewers use are found. Unexposed viewers are matched with pricing and media avails from one or more media directories. Media avails are then analyzed along with incremental on-target impressions. Targeted avails for unexposed viewers are then determined, based on lowest incremental cost and largest incremental reach are added to a current cross-screen plan. An analysis to find new unexposed viewers is then re-run to determine the next-most cost effective avails. The above steps are repeated or looped until a selected advertisement budget has been allocated. User interface embodiments for these methods are also disclosed.Type: GrantFiled: September 30, 2016Date of Patent: October 15, 2019Assignee: ADOBE INC.Inventors: Antoine Barbier, Greg Collison, Albert Lim, Nikhil Belsare, Alexander R. Hood
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Publication number: 20190303964Abstract: Systems and methods are disclosed for enabling incremental reach for an advertising campaign, across multiple screens/channels. In some embodiments, a base TV/media plan is uploaded, and targeted exposed viewers are monitored. Unexposed target viewers are identified. Additional media channels that unexposed viewers use are found. Unexposed viewers are matched with pricing and media avails from one or more media directories. Media avails are then analyzed along with incremental on-target impressions. Targeted avails for unexposed viewers are then determined, based on lowest incremental cost and largest incremental reach are added to a current cross-screen plan. An analysis to find new unexposed viewers is then re-run to determine the next-most cost effective avails. The above steps are repeated or looped until a selected advertisement budget has been allocated. User interface embodiments for these methods are also disclosed.Type: ApplicationFiled: June 12, 2019Publication date: October 3, 2019Inventors: Antoine Barbier, Greg Collison, Albert Lim, Nikhil Belsare, Alexander R. Hood