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公开(公告)号：US12206925B2
公开(公告)日：2025-01-21
申请号：US17813622
申请日：2022-07-20
Applicant: ADOBE INC.
Inventor： Atanu R. Sinha , Aurghya Maiti , Atishay Ganesh , Saili Myana , Harshita Chopra , Sarthak Kapoor , Saurabh Mahapatra
IPC: H04N21/25 , H04N21/2668
Abstract: Systems and methods for content customization are provided. One aspect of the systems and methods includes receiving dynamic characteristics for a plurality of users, wherein the dynamic characteristics include interactions between the plurality of users and a digital content channel; clustering the plurality of users in a plurality of segments based on the dynamic characteristics using a machine learning model; assigning a user to a segment of the plurality of segments based on static characteristics of the user; and providing customized digital content for the user based on the segment.
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公开(公告)号：US12182829B2
公开(公告)日：2024-12-31
申请号：US17849320
申请日：2022-06-24
Applicant: Adobe Inc.
Inventor： Sarthak Chakraborty , Sunav Choudhary , Atanu R. Sinha , Sapthotharan Krishnan Nair , Manoj Ghuhan Arivazhagan , Yuvraj , Atharva Anand Joshi , Atharv Tyagi , Shivi Gupta
IPC: G06Q30/0201 , G06N3/04 , G06Q30/0251
Abstract: A system includes a representation generator subsystem configured to execute a user representation model and a task prediction model to generate a user representation for a user. The user representation model receives user event sequence data comprises a sequence of user interactions with the system. The task prediction model is configured to train the user representation model. The user representation includes a vector of a predetermined size that represents the user event sequence data and is generated by applying the trained user representation model to the user event sequence data. A storage requirement of the user representation is less than a storage space requirement of the user event sequence data. The system includes a data store configured for storing the user representation in a user profile associated with the user.
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公开(公告)号：US12124948B2
公开(公告)日：2024-10-22
申请号：US17236506
申请日：2021-04-21
Applicant: Adobe Inc.
Inventor： Atanu R. Sinha , Deepali Jain , Nikhil Sheoran , Deepali Gupta , Sopan Khosla
Abstract: In some embodiments, a computing system computes, with a state prediction model, probabilities of transitioning from a click state represented by interaction data to various predicted next states. The computing system computes an interface experience metric for the click with an experience valuation model. To do so, the computing system identifies base values for the click state and the predicted next states. The computing system computes value differentials for between the click state's base value and each predicted next state's base value. Value differentials indicate qualities of interface experience. The computing system determines the interface experience metric from a summation that includes the current click state's base value and the value differentials weighted with the predicted next states' probabilities. The computing system transmits the interface experience metric to an online platform, which can cause interface elements of the online platform to be modified based on the interface experience metric.
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4.发明公开公开(公告)号：US20240135296A1
公开(公告)日：2024-04-25
申请号：US17969643
申请日：2022-10-18
Applicant: Adobe Inc.
Inventor： Atanu R. Sinha , Shiv Kumar Saini , Prithvi Bhutani , Nikhil Sheoran , Kevin Cobourn , Jeff D. Chasin , Fan Du , Eric Matisoff
IPC: G06Q10/0639 , G06F3/0484
CPC classification number: G06Q10/06393 , G06F3/0484
Abstract: In some examples, an environment evaluation system accesses interaction data recording interactions by users with an online platform hosted by a host system and computes, based on the interaction data, interface experience metrics. The interface experience metrics includes an individual experience metric for each user and a transition experience metric for each transition in the interactions by the users with the online platform. The environment evaluation system identifies a user with the individual experience metric below a pre-determined threshold, identifies a transition performed by the user that has a transition experience metric below a second threshold, and analyzes the transition to determine users who have performed the transition. The environment evaluation system updates the host system with the individual experience metrics and the transition metrics, based on which the host system can perform modifications of interface elements of the online platform to improve the experience.
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5.发明授权公开(公告)号：US11038785B2
公开(公告)日：2021-06-15
申请号：US16253467
申请日：2019-01-22
Applicant: Adobe Inc.
Inventor： Pranav Ravindra Maneriker , Reshmi Sasidharan , Atanu R. Sinha
Abstract: In some embodiments, an intervention evaluation system estimates counterfactual metric for a focal online platform based on an assessment model built using performance data of the focal online platform and control online platforms. The intervention evaluation system accesses performance data of the focal online platform that has been subject to a temporary intervention and performance data of control online platforms that are not subject to the temporary intervention. The intervention evaluation system determines estimation weights for these control online platforms based on the performance data in a pre-intervention period. Based on the estimation weights, the intervention evaluation system computes a counterfactual metric indicating the performance of the focal online platform in a post-intervention period in the absence of the temporary intervention. The counterfactual metric is transmitted to the focal online platform, where the counterfactual metric is usable for modifying an interactive computing environment provided by the focal online platform.
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Patent Agency Ranking
公开(公告)号：US20230259403A1
公开(公告)日：2023-08-17
申请号：US17674578
申请日：2022-02-17
Applicant: Adobe Inc.
Inventor： Atanu R. Sinha , Shiv Kumar Saini , Sapthotharan Krishnan Nair , Saarthak Sandip Marathe , Manupriya Gupta , Brahmbhatt Paresh Anand , Ayush Chauhan
CPC classification number: G06F9/5055 , H04L67/10 , H04L47/826
Abstract: In implementations of systems for cloud-based resource allocation using meters, a computing device implements a resource system to receive resource data describing an amount of cloud-based resources reserved for consumption by client devices during a period of time and a total amount of cloud-based resources consumed by the client devices during the period of time. The resource system determines a consumption distribution using each meter included in a set of meters. Each of the consumption distributions allocates a portion of the total amount of the cloud-based resources consumed to each client device of the client devices. A particular meter used to determine a particular consumption distribution is selected based on a Kendall Tau coefficient of the particular consumption distribution. An amount of cloud-based resources to allocate for a future period of time is estimated using the particular meter and an approximate Shapley value.
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公开(公告)号：US20220394337A1
公开(公告)日：2022-12-08
申请号：US17339700
申请日：2021-06-04
Applicant: Adobe Inc.
Inventor： Liana Vagharshakian , Atanu R. Sinha , Camille Girabawe , Gautam Choudhary , Omar Rahman , Scott Trafton , Vivek Sinha
IPC: H04N21/466 , H04N21/45 , H04N21/258
Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately and efficiently predicting conversion probability scores and key personas for target entities utilizing an artificial intelligence approach. For example, the disclosed systems utilize a conversion activity score neural network to predict conversion activity probability scores for target entities and utilize a persona prediction machine learning model to predict key personas associated with target entities. In particular, the disclosed systems utilize the conversion activity score neural network to generate a predicted conversion activity probability score for a target entity from input data including client device interactions of digital profiles belonging to the target entity as well as an entity feature vector representing characteristics of the target entity. The disclosed systems also (or alternatively) utilize a persona prediction machine learning model to determine a set of key personas for the target entity from the entity feature vector.
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公开(公告)号：US20210241158A1
公开(公告)日：2021-08-05
申请号：US17236506
申请日：2021-04-21
Applicant: Adobe Inc.
Inventor： Atanu R. Sinha , Deepali Jain , Nikhil Sheoran , Deepali Gupta , Sopan Khosla
Abstract: In some embodiments, a computing system computes, with a state prediction model, probabilities of transitioning from a click state represented by interaction data to various predicted next states. The computing system computes an interface experience metric for the click with an experience valuation model. To do so, the computing system identifies base values for the click state and the predicted next states. The computing system computes value differentials for between the click state's base value and each predicted next state's base value. Value differentials indicate qualities of interface experience. The computing system determines the interface experience metric from a summation that includes the current click state's base value and the value differentials weighted with the predicted next states' probabilities. The computing system transmits the interface experience metric to an online platform, which can cause interface elements of the online platform to be modified based on the interface experience metric.
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公开(公告)号：US10929438B2
公开(公告)日：2021-02-23
申请号：US16008601
申请日：2018-06-14
Applicant: Adobe Inc.
Inventor： Ritwik Sinha , Pranav Ravindra Maneriker , Dhruv Singal , Atanu R. Sinha
IPC: G06F7/00 , G06F16/28 , G06F16/25 , G06F16/2457
Abstract: Systems and techniques for identifying segments in categorical data include receiving multiple transaction ID (TID) lists with univariate values that satisfy a thresholding metric with each TID list representing an occurrence of a single attribute in a set of transactions. The TID lists are stored with the univariate values that satisfy the thresholding metric in a data structure. In a loop, candidate itemsets to form from combinations of TID lists are determined using only the combinations of TID lists that satisfy categorical constraints. In the loop, for the candidate itemsets that satisfy categorical constraints, both the thresholding metric and a similarity metric are applied to the candidate itemsets. Final itemsets are formed from only the candidate itemsets that satisfy both the thresholding metric and the similarity metric.
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公开(公告)号：US20190384853A1
公开(公告)日：2019-12-19
申请号：US16008601
申请日：2018-06-14
Applicant: Adobe Inc.
Inventor： Ritwik Sinha , Pranav Ravindra Maneriker , Dhruv Singal , Atanu R. Sinha
IPC: G06F17/30
Abstract: Systems and techniques for identifying segments in categorical data include receiving multiple transaction ID (TID) lists with univariate values that satisfy a thresholding metric with each TID list representing an occurrence of a single attribute in a set of transactions. The TID lists are stored with the univariate values that satisfy the thresholding metric in a data structure. In a loop, candidate itemsets to form from combinations of TID lists are determined using only the combinations of TID lists that satisfy categorical constraints. In the loop, for the candidate itemsets that satisfy categorical constraints, both the thresholding metric and a similarity metric are applied to the candidate itemsets. Final itemsets are formed from only the candidate itemsets that satisfy both the thresholding metric and the similarity metric.
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