Patents by Inventor Sunpreet Singh Khanuja
Sunpreet Singh Khanuja 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: 11972455Abstract: Systems, methods and media for adaptive real time modeling and scoring are provided. In one example, a system for automatically generating predictive scoring models comprises a trigger component to determine, based on a threshold or trigger, such as a detection of new significant relationships, whether a predictive scoring model is ready for a refresh or regeneration. An automated modeling sufficiency checker receives and transforms user-selectable system input data. The user-selectable system input data may comprise at least one of email, display or social media traffic. An adaptive modeling engine operably connected to the trigger component and modeling sufficiency checker is configured to monitor and identify a change in the input data and, based on an identified change in the input data, automatically refresh or regenerate the scoring model for calculating new lead scores. A refreshed or regenerated predictive scoring model is output.Type: GrantFiled: November 30, 2021Date of Patent: April 30, 2024Assignee: Zeta Global Corp.Inventors: Pavan Korada, Sunpreet Singh Khanuja, Yun Sam Chong, Bharat Goyal, Edward Robert Rau, Jr.
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Publication number: 20220245667Abstract: Various examples are directed to systems and methods for adaptively generating leads. A marketing system may determine that a first lead score for a first lead is greater than a first lead score threshold and determine that a second lead score for a second lead is less than the first lead score threshold. The marketing system may generate a set of filtered leads including the first lead information from the first lead. The marketing system may determine a scrub rate that describes a portion of first execution cycle data having lead scores greater than the first lead score threshold and determine that the scrub rate is greater than an analysis window scrub rate by more than a scrub rate threshold. The marketing system may select a second lead score threshold that is lower than the first lead score threshold.Type: ApplicationFiled: April 22, 2022Publication date: August 4, 2022Inventors: Pavan Korada, Sunpreet Singh Khanuja, Weiwei Zhang, Bharat Goyal
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Patent number: 11354700Abstract: Various examples are directed to systems and methods for adaptively generating leads. A marketing system may determine that a first lead score for a first lead is greater than a first lead score threshold and determine that a second lead score for a second lead is less than the first lead score threshold. The marketing system may generate a set of filtered leads including the first lead information from the first lead. The marketing system may determine a scrub rate that describes a portion of first execution cycle data having lead scores greater than the first lead score threshold and determine that the scrub rate is greater than an analysis window scrub rate by more than a scrub rate threshold. The marketing system may select a second lead score threshold that is lower than the first lead score threshold.Type: GrantFiled: June 26, 2019Date of Patent: June 7, 2022Assignee: Zeta Global Corp.Inventors: Pavan Korada, Sunpreet Singh Khanuja, Weiwei Zhang, Bharat Goyal
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Publication number: 20220114497Abstract: In some examples, special-purpose machines are provided that facilitate smart copy optimization in a network service or publication system, including software-configured computerized variants of such special-purpose machines and improvements to such variants, and to the technologies by which such special-purpose machines become improved compared to other special-purpose machines that facilitate adding the new features. Such technologies can include special artificial-intelligence (AI), machine-learning (ML), and natural-language-processing (NLP) techniques.Type: ApplicationFiled: December 22, 2021Publication date: April 14, 2022Inventors: Pavan Korada, Sunpreet Singh Khanuja, Ao Li
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Patent number: 11295237Abstract: In some examples, special-purpose machines are provided that facilitate smart copy optimization in a network service or publication system, including software-configured computerized variants of such special-purpose machines and improvements to such variants, and to the technologies by which such special-purpose machines become improved compared to other special-purpose machines that facilitate adding the new features. Such technologies can include special artificial-intelligence (AI), machine-learning (ML), and natural-language-processing (NLP) techniques.Type: GrantFiled: December 14, 2018Date of Patent: April 5, 2022Assignee: Zeta Global Corp.Inventors: Pavan Korada, Sunpreet Singh Khanuja, Ao Li
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Publication number: 20220092635Abstract: Systems, methods and media for adaptive real time modeling and scoring are provided. In one example, a system for automatically generating predictive scoring models comprises a trigger component to determine, based on a threshold or trigger, such as a detection of new significant relationships, whether a predictive scoring model is ready for a refresh or regeneration. An automated modeling sufficiency checker receives and transforms user-selectable system input data. The user-selectable system input data may comprise at least one of email, display or social media traffic. An adaptive modeling engine operably connected to the trigger component and modeling sufficiency checker is configured to monitor and identify a change in the input data and, based on an identified change in the input data, automatically refresh or regenerate the scoring model for calculating new lead scores. A refreshed or regenerated predictive scoring model is output.Type: ApplicationFiled: November 30, 2021Publication date: March 24, 2022Inventors: Pavan Korada, Sunpreet Singh Khanuja, Yun Sam Chong, Bharat Goyal, Edward Robert Rau, JR.
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Publication number: 20220027943Abstract: Various examples are directed to systems and methods for adaptively generating leads. A marketing system may determine that a first lead score for a first lead is greater than a first lead score threshold and determine that a second lead score for a second lead is less than the first lead score threshold. The marketing system may generate a set of filtered leads including the first lead information from the first lead. The marketing system may determine a scrub rate that describes a portion of first execution cycle data having lead scores greater than the first lead score threshold and determine that the scrub rate is greater than an analysis window scrub rate by more than a scrub rate threshold. The marketing system may select a second lead score threshold that is lower than the first lead score threshold.Type: ApplicationFiled: October 11, 2021Publication date: January 27, 2022Inventors: Pavan Korada, Sunpreet Singh Khanuja, Weiwei Zhang, Bharat Goyal
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Patent number: 11227304Abstract: Systems, methods and media for adaptive real time modeling and scoring are provided. In one example, a system for automatically generating predictive scoring models comprises a trigger component to determine, based on a threshold or trigger, such as a detection of new significant relationships, whether a predictive scoring model is ready for a refresh or regeneration. An automated modeling sufficiency checker receives and transforms user-selectable system input data. The user-selectable system input data may comprise at least one of email, display or social media traffic. An adaptive modeling engine operably connected to the trigger component and modeling sufficiency checker is configured to monitor and identify a change in the input data and, based on an identified change in the input data, automatically refresh or regenerate the scoring model for calculating new lead scores. A refreshed or regenerated predictive scoring model is output.Type: GrantFiled: May 12, 2017Date of Patent: January 18, 2022Assignee: Zeta Global Corp.Inventors: Pavan Korada, Sunpreet Singh Khanuja, Yun Sam Chong, Bharat Goyal, Edward Robert Rau, Jr.
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Patent number: 11144949Abstract: Various examples are directed to systems and methods for adaptively generating leads. A marketing system may determine that a first lead score for a first lead is greater than a first lead score threshold and determine that a second lead score for a second lead is less than the first lead score threshold. The marketing system may generate a set of filtered leads including the first lead information from the first lead. The marketing system may determine a scrub rate that describes a portion of first execution cycle data having lead scores greater than the first lead score threshold and determine that the scrub rate is greater than an analysis window scrub rate by more than a scrub rate threshold. The marketing system may select a second lead score threshold that is lower than the first lead score threshold.Type: GrantFiled: May 12, 2017Date of Patent: October 12, 2021Inventors: Pavan Korada, Sunpreet Singh Khanuja, Weiwei Zhang, Bharat Goyal
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Publication number: 20200193322Abstract: In some examples, special-purpose machines are provided that facilitate smart copy optimization in a network service or publication system, including software-configured computerized variants of such special-purpose machines and improvements to such variants, and to the technologies by which such special-purpose machines become improved compared to other special-purpose machines that facilitate adding the new features. Such technologies can include special artificial-intelligence (AI), machine-learning (ML), and natural-language-processing (NLP) techniques.Type: ApplicationFiled: December 14, 2018Publication date: June 18, 2020Inventors: Pavan Korada, Sunpreet Singh Khanuja, Ao Li
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Publication number: 20190318378Abstract: Various examples are directed to systems and methods for adaptively generating leads. A marketing system may determine that a first lead score for a first lead is greater than a first lead score threshold and determine that a second lead score for a second lead is less than the first lead score threshold. The marketing system may generate a set of filtered leads including the first lead information from the first lead. The marketing system may determine a scrub rate that describes a portion of first execution cycle data having lead scores greater than the first lead score threshold and determine that the scrub rate is greater than an analysis window scrub rate by more than a scrub rate threshold. The marketing system may select a second lead score threshold that is lower than the first lead score threshold.Type: ApplicationFiled: June 26, 2019Publication date: October 17, 2019Inventors: Pavan Korada, Sunpreet Singh Khanuja, Weiwei Zhang, Bharat Goyal
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Publication number: 20170330220Abstract: Various examples are directed to systems and methods for adaptively generating leads. A marketing system may determine that a first lead score for a first lead is greater than a first lead score threshold and determine that a second lead score for a second lead is less than the first lead score threshold. The marketing system may generate a set of filtered leads including the first lead information from the first lead. The marketing system may determine a scrub rate that describes a portion of first execution cycle data having lead scores greater than the first lead score threshold and determine that the scrub rate is greater than an analysis window scrub rate by more than a scrub rate threshold. The marketing system may select a second lead score threshold that is lower than the first lead score threshold.Type: ApplicationFiled: May 12, 2017Publication date: November 16, 2017Inventors: Pavan Korada, Sunpreet Singh Khanuja, Weiwei Zhang, Bharat Goyal
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Publication number: 20170329881Abstract: Systems, methods and media for adaptive real time modeling and scoring are provided. In one example, a system for automatically generating predictive scoring models comprises a trigger component to determine, based on a threshold or trigger, such as a detection of new significant relationships, whether a predictive scoring model is ready for a refresh or regeneration. An automated modeling sufficiency checker receives and transforms user-selectable system input data. The user-selectable system input data may comprise at least one of email, display or social media traffic. An adaptive modeling engine operably connected to the trigger component and modeling sufficiency checker is configured to monitor and identify a change in the input data and, based on an identified change in the input data, automatically refresh or regenerate the scoring model for calculating new lead scores. A refreshed or regenerated predictive scoring model is output.Type: ApplicationFiled: May 12, 2017Publication date: November 16, 2017Inventors: Pavan Korada, Sunpreet Singh Khanuja, Yun Sam Chong, Bharat Goyal, Edward Robert Rau, JR.