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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
申请人： Adobe Inc.
发明人： Atanu R. Sinha , Deepali Jain , Nikhil Sheoran , Deepali Gupta , Sopan Khosla
摘要： 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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2.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
申请人： Adobe Inc.
发明人： Atanu R. Sinha , Shiv Kumar Saini , Prithvi Bhutani , Nikhil Sheoran , Kevin Cobourn , Jeff D. Chasin , Fan Du , Eric Matisoff
IPC分类号： G06Q10/0639 , G06F3/0484
CPC分类号： G06Q10/06393 , G06F3/0484
摘要： 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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3.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
申请人： Adobe Inc.
摘要： 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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公开(公告)号：US20230259403A1
公开(公告)日：2023-08-17
申请号：US17674578
申请日：2022-02-17
申请人： Adobe Inc.
发明人： Atanu R. Sinha , Shiv Kumar Saini , Sapthotharan Krishnan Nair , Saarthak Sandip Marathe , Manupriya Gupta , Brahmbhatt Paresh Anand , Ayush Chauhan
CPC分类号： G06F9/5055 , H04L67/10 , H04L47/826
摘要： 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
申请人： Adobe Inc.
发明人： Liana Vagharshakian , Atanu R. Sinha , Camille Girabawe , Gautam Choudhary , Omar Rahman , Scott Trafton , Vivek Sinha
IPC分类号： H04N21/466 , H04N21/45 , H04N21/258
摘要： 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
申请人： Adobe Inc.
发明人： Atanu R. Sinha , Deepali Jain , Nikhil Sheoran , Deepali Gupta , Sopan Khosla
摘要： 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
申请人： Adobe Inc.
IPC分类号： G06F7/00 , G06F16/28 , G06F16/25 , G06F16/2457
摘要： 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
申请人： Adobe Inc.
IPC分类号： G06F17/30
摘要： 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：US20240303176A1
公开(公告)日：2024-09-12
申请号：US18178715
申请日：2023-03-06
申请人： Adobe Inc.
发明人： Raunak Shah , Shiv Kumar Saini , Atanu R. Sinha
CPC分类号： G06F11/3442 , G06F9/5077
摘要： A computing resource allocation system receives entity resource usage data describing computing resource usage of an executable service platform by an entity as part of a first allocation generated using a first allocation mechanism. A computing resource allocation system generates an entity resource model based on the entity resource usage data of the computing resource usage of the executable service platform as part of the first allocation mechanism. A computing resource allocation system simulates computing resource usage of the executable service platform by the entity as part of a second allocation mechanism based on the entity resource model and the entity resource usage data. A computing resource allocation system estimates a second allocation to provide to the entity based on the simulating.
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公开(公告)号：US12086646B2
公开(公告)日：2024-09-10
申请号：US17674578
申请日：2022-02-17
申请人： Adobe Inc.
发明人： Atanu R. Sinha , Shiv Kumar Saini , Sapthotharan Krishnan Nair , Saarthak Sandip Marathe , Manupriya Gupta , Brahmbhatt Paresh Anand , Ayush Chauhan
CPC分类号： G06F9/5055 , H04L47/826 , H04L67/10
摘要： 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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