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公开(公告)号：US10546003B2
公开(公告)日：2020-01-28
申请号：US15808498
申请日：2017-11-09
Applicant: Adobe Inc.
Inventor： Prakhar Gupta , Iftikhar Ahamath Burhanuddin , Harvineet Singh , Atanu Ranjan Sinha
IPC: G06F16/33 , G06F16/242 , G06F16/332 , G10L15/22 , G10L15/26
Abstract: This disclosure covers methods, non-transitory computer readable media, and systems that use an intelligent analytics interface to process natural-language and other inputs to configure an analytics task for the system. The disclosed methods, non-transitory computer readable media, and systems provide the intelligent analytics interface to facilitate an exchange between the systems and a user to determine values for the analytics task. The methods, non-transitory computer readable media, and systems then use these values to execute an analytics task.
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公开(公告)号：US20190138648A1
公开(公告)日：2019-05-09
申请号：US15808498
申请日：2017-11-09
Applicant: Adobe Inc.
Inventor： Prakhar Gupta , Iftikhar Ahamath Burhanuddin , Harvineet Singh , Atanu Ranjan Sinha
Abstract: This disclosure covers methods, non-transitory computer readable media, and systems that use an intelligent analytics interface to process natural-language and other inputs to configure an analytics task for the system. The disclosed methods, non-transitory computer readable media, and systems provide the intelligent analytics interface to facilitate an exchange between the systems and a user to determine values for the analytics task. The methods, non-transitory computer readable media, and systems then use these values to execute an analytics task.
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3.发明申请公开(公告)号：US20220012703A1
公开(公告)日：2022-01-13
申请号：US17449124
申请日：2021-09-28
Applicant: Adobe Inc.
Inventor： Shiv Kumar Saini , Ritwick Chaudhry , Harvineet Singh , Bhavya Bahl , Sriya Sainath , Savya Sindhu Gupta
Abstract: Techniques for exchanging data segments between data aggregators and data consumers. In an embodiment, a value of an arbitrary data segment selected by a data consumer is computed. In particular, an individual user value is calculated for each user represented in the data segment, wherein the individual user value is a weighted sum (or other function) of the one or more features of the data segment attributable to that user, plus an additive gaussian noise. The overall value of the data segment is the sum of the individual user values. An offer price for the data segment can then be calculated using the overall value. Once a request is received from the consumer to purchase the data segment at the offer price, the data segment can be exchanged between the aggregator and consumer. Thus, a data marketplace or platform for the exchange of data segments is enabled.
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4.发明授权公开(公告)号：US11151532B2
公开(公告)日：2021-10-19
申请号：US16788841
申请日：2020-02-12
Applicant: Adobe Inc.
Inventor： Shiv Kumar Saini , Ritwick Chaudhry , Harvineet Singh , Bhavya Bahl , Sriya Sainath , Savya Sindhu Gupta
Abstract: Techniques for exchanging data segments between data aggregators and data consumers. In an embodiment, a value of an arbitrary data segment selected by a data consumer is computed. In particular, an individual user value is calculated for each user represented in the data segment, wherein the individual user value is a weighted sum (or other function) of the one or more features of the data segment attributable to that user, plus an additive gaussian noise. The overall value of the data segment is the sum of the individual user values. An offer price for the data segment can then be calculated using the overall value. Once a request is received from the consumer to purchase the data segment at the offer price, the data segment can be exchanged between the aggregator and consumer. Thus, a data marketplace or platform for the exchange of data segments is enabled.
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公开(公告)号：US10984058B2
公开(公告)日：2021-04-20
申请号：US15892085
申请日：2018-02-08
Applicant: Adobe Inc.
Inventor： Branislav Kveton , Zheng Wen , Prakhar Gupta , Iftikhar Ahamath Burhanuddin , Harvineet Singh , Gaurush Hiranandani
IPC: G06F16/00 , G06F16/9535 , G06N20/00 , G06F16/248 , G06F16/2457 , G06Q30/02
Abstract: A machine-learning framework uses partial-click feedback to generate an optimal diverse set of items. An example method includes estimating a preference vector for a user based on diverse cascade statistics for the user, the diverse cascade statistics including previously observed responses and previously observed topic gains. The method also includes generating an ordered set of items from the item repository, the items in the ordered set having highest topic gain weighted by similarity with the preference vector, providing the ordered set for presentation to the user, and receiving feedback from the user on the ordered set. The method also includes, responsive to the feedback indicating a selected item, updating the diverse cascade statistics for observed items, wherein the updating results in penalizing the topic gain for items of the observed items that are not the selected item and promoting the topic gain for the selected item.
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Patent Agency Ranking
公开(公告)号：US20190243923A1
公开(公告)日：2019-08-08
申请号：US15892085
申请日：2018-02-08
Applicant: Adobe Inc.
Inventor： Branislav Kveton , Zheng Wen , Prakhar Gupta , Iftikhar Ahamath Burhanuddin , Harvineet Singh , Gaurush Hiranandani
CPC classification number: G06F16/9535 , G06F16/24578 , G06F16/248 , G06N20/00
Abstract: A machine-learning framework uses partial-click feedback to generate an optimal diverse set of items. An example method includes estimating a preference vector for a user based on diverse cascade statistics for the user, the diverse cascade statistics including previously observed responses and previously observed topic gains. The method also includes generating an ordered set of items from the item repository, the items in the ordered set having highest topic gain weighted by similarity with the preference vector, providing the ordered set for presentation to the user, and receiving feedback from the user on the ordered set. The method also includes, responsive to the feedback indicating a selected item, updating the diverse cascade statistics for observed items, wherein the updating results in penalizing the topic gain for items of the observed items that are not the selected item and promoting the topic gain for the selected item.
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公开(公告)号：US20190087861A1
公开(公告)日：2019-03-21
申请号：US16192517
申请日：2018-11-15
Applicant: Adobe Inc.
IPC: G06Q30/02
Abstract: The present disclosure is directed toward systems and methods for generating an un-subscription model and predicting whether a potential customer will un-subscribe from receiving electronic marketing content from a marketing source. For example, systems and methods described herein involve generating a prediction un-subscription model that predicts whether a potential customer is prone to un-subscribe from receiving future communications about a product or merchant in response to receiving a communication for the product or merchant. The systems and methods further involve determining an appropriate action to take with regard to a potential customer based on whether the potential customer is prone to un-subscribe from receiving future communications.
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公开(公告)号：US11321373B2
公开(公告)日：2022-05-03
申请号：US16698383
申请日：2019-11-27
Applicant: Adobe Inc.
Inventor： Prakhar Gupta , Iftikhar Ahamath Burhanuddin , Harvineet Singh , Atanu Ranjan Sinha
IPC: G06F16/33 , G06F16/242 , G06F16/332 , G10L15/22 , H04L51/02 , G06F40/30 , G10L15/26
Abstract: This disclosure covers methods, non-transitory computer readable media, and systems that use an intelligent analytics interface to process natural-language and other inputs to configure an analytics task for the system. The disclosed methods, non-transitory computer readable media, and systems provide the intelligent analytics interface to facilitate an exchange between the systems and a user to determine values for the analytics task. The methods, non-transitory computer readable media, and systems then use these values to execute an analytics task.
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公开(公告)号：US11170407B2
公开(公告)日：2021-11-09
申请号：US16192517
申请日：2018-11-15
Applicant: Adobe Inc.
IPC: G06Q30/02
Abstract: The present disclosure is directed toward systems and methods for generating an un-subscription model and predicting whether a potential customer will un-subscribe from receiving electronic marketing content from a marketing source. For example, systems and methods described herein involve generating a prediction un-subscription model that predicts whether a potential customer is prone to un-subscribe from receiving future communications about a product or merchant in response to receiving a communication for the product or merchant. The systems and methods further involve determining an appropriate action to take with regard to a potential customer based on whether the potential customer is prone to un-subscribe from receiving future communications.
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公开(公告)号：US20190138944A1
公开(公告)日：2019-05-09
申请号：US15808171
申请日：2017-11-09
Applicant: Adobe Inc.
Inventor： Moumita Sinha , Vishwa Vinay , Harvineet Singh , Frederic Mary
IPC: G06N99/00
Abstract: The present disclosure relates applying a survival analysis to model when a particular recipient will view an electronic message. For example, one or more embodiments train a survivor function to model the time that will elapse, on a continuous scale, before a recipient will open an electronic message. For example, one or more embodiments involve accessing analytics training data and extracting a first set of features affecting the time that elapsed before past recipients opened an electronic message and a second set of features affecting whether the recipients opened the electronic message at all. The system then generates a mixture model modified survivor function and determines the effect of each feature set on its corresponding outcome to learn parameters for the mixture model modified survivor function.
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