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21.发明申请公开(公告)号：US20220214957A1
公开(公告)日：2022-07-07
申请号：US17703188
申请日：2022-03-24
Applicant: Adobe Inc.
Inventor： Meghanath M Y , Shankar Venkitachalam , Deepak Pai
Abstract: In some embodiments, a computing system identifies a current engagement stage of a user with an online platform by applying a stage prediction model based on interaction data associated with the user. The interaction data describe actions performed by the user with respect to the online platform and context data associated with each of the actions. The computing system further identifies one or more critical events for promoting the user to transition from one engagement stage to a higher engagement stage based on the interaction data associated with the user. The computing system can make the identified current engagement stage of the user or the identified critical event to be accessible by the online platform so that user interfaces presented on the online platform can be modified to improve a likelihood of the user to transit from the current stage to a higher engagement stage.
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公开(公告)号：US11080745B2
公开(公告)日：2021-08-03
申请号：US15435869
申请日：2017-02-17
Applicant: Adobe Inc.
Inventor： Ritwik Sinha , Kushal Chawla , Yash Shrivastava , Dhruv Singal , Atanu Ranjan Sinha , Deepak Pai
IPC: G06Q30/02
Abstract: Forecasting a potential audience size and an unduplicated audience size for a digital campaign includes receiving an audience segment input and a time period input. The audience segment input is converted into multiple atomic target specifications. For each of the multiple atomic target specifications, a potential audience size is determined during the time period input by selecting a time series model based on a frequency of attribute values from the atomic target specification and combining the selected time series model with a frequent item set model. The potential audience size for each of atomic target specifications is aggregated over the time period input into a total potential audience size. The total potential audience size is output. The time series model and the frequent item set model are obtained using data from a historic bid request database.
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公开(公告)号：US10666748B2
公开(公告)日：2020-05-26
申请号：US14451148
申请日：2014-08-04
Applicant: ADOBE INC.
Inventor： Craig Mathis , James Harold Brown , Joshua Aaron Hansen , Deepak Pai
IPC: H04L29/08 , G06F3/0481
Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed to an analytics tool for detecting real-time user or “visitor” events based on real-time data. More specifically, events are detected based on actions not taken by a user. In this regard, events can be defined and, thereafter, detected based on inactions of a user. In some cases, events are inferred or predicted based on a calculated likelihood of a user not performing an action. Upon determining an event based on an action not being performed by a user, an interested party may be notified thereof such that the interested party can influence, in real-time, visitor conversion.
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公开(公告)号：US12190621B2
公开(公告)日：2025-01-07
申请号：US17653414
申请日：2022-03-03
Applicant: Adobe Inc.
Inventor： Debraj Debashish Basu , Shankar Venkitachalam , Vinh Khuc , Deepak Pai
IPC: G06F17/00 , G06F40/295 , G06N20/00 , G06V30/19 , G06V30/416
Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media that utilize intelligent contextual bias weights for informing keyphrase relevance models to extract keyphrases. For example, the disclosed systems generate a graph from a digital document by mapping words from the digital document to nodes of the graph. In addition, the disclosed systems determine named entity bias weights for the nodes of the graph utilizing frequencies with which the words corresponding to the nodes appear within named entities identified from the digital document. Moreover, the disclosed systems generate a keyphrase summary for the digital document utilizing the graph and a machine learning model biased according to the named entity bias weights for the nodes of the graph.
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公开(公告)号：US20240312087A1
公开(公告)日：2024-09-19
申请号：US18360919
申请日：2023-07-28
Applicant: ADOBE INC.
Inventor： Shradha Agrawal , Debraj Debashish Basu , Deepak Pai , Nimish Srivastav , Meghanath Macha , Ambareesh Revanur
IPC: G06T11/60 , G06F40/186 , G06F40/40 , G06Q30/0241 , G06T7/90
CPC classification number: G06T11/60 , G06F40/186 , G06F40/40 , G06Q30/0276 , G06T7/90 , G06T2207/10024 , G06T2207/20081
Abstract: Systems and methods for document processing are provided. One aspect of the systems and methods includes identifying a theme and an input image of a product. Another aspect of the systems and methods includes generating an output image depicting the product and the theme based on the input image using an image generation model that is trained to generate images consistent with a brand. Another aspect of the systems and methods includes generating text based on the product and the theme using a text generation model. Another aspect of the systems and methods includes generating custom content consistent with the brand and the theme based on the output image and the text.
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Patent Agency Ranking
26.发明授权公开(公告)号：US11580420B2
公开(公告)日：2023-02-14
申请号：US16253892
申请日：2019-01-22
Applicant: Adobe Inc.
Inventor： Deepak Pai , Joshua Sweetkind-Singer , Debraj Basu
Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for analyzing feature impact of a machine-learning model using prototypes across analytical spaces. For example, the disclosed system can identify features of data points used to generate outputs via a machine-learning model and then map the features to a feature space and the outputs to a label space. The disclosed system can then utilize an iterative process to determine prototypes from the data points based on distances between the data points in the feature space and the label space. Furthermore, the disclosed system can then use the prototypes to determine the impact of the features within the machine-learning model based on locally sensitive directions; region variability; or mean, range, and variance of features of the prototypes.
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27.发明授权公开(公告)号：US11314616B2
公开(公告)日：2022-04-26
申请号：US16775815
申请日：2020-01-29
Applicant: Adobe Inc.
Inventor： Meghanath M Y , Shankar Venkitachalam , Deepak Pai
Abstract: In some embodiments, a computing system identifies a current engagement stage of a user with an online platform by applying a stage prediction model based on interaction data associated with the user. The interaction data describe actions performed by the user with respect to the online platform and context data associated with each of the actions. The computing system further identifies one or more critical events for promoting the user to transition from one engagement stage to a higher engagement stage based on the interaction data associated with the user. The computing system can make the identified current engagement stage of the user or the identified critical event to be accessible by the online platform so that user interfaces presented on the online platform can be modified to improve a likelihood of the user to transit from the current stage to a higher engagement stage.
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公开(公告)号：US11176713B2
公开(公告)日：2021-11-16
申请号：US16778906
申请日：2020-01-31
Applicant: ADOBE INC.
Inventor： Shradha Agrawal , Deepak Pai , Dhanya Raghu
Abstract: Embodiments of the present disclosure are directed towards generating images conditioned on a desired attribute. In particular, an attribute-based image generation system can use a directional-GAN architecture to generate images conditioned on a desired attribute. A latent vector and a desired attribute are received. A feature subspace is determined for the latent vector using a latent-attribute linear classifier trained to determine a relationship between the latent vector and the desired attribute. An image is generated using the latent vector such that the image contains the desired attribute. In embodiments, where the feature space differs from a desired feature subspace, a directional vector is applied to the latent vector that shifts the latent vector from the feature subspace to the desired feature subspace. This modified latent vector is then used during generation of the image.
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公开(公告)号：US20210241497A1
公开(公告)日：2021-08-05
申请号：US16778906
申请日：2020-01-31
Applicant: ADOBE INC.
Inventor： Shradha Agrawal , Deepak Pai , Dhanya Raghu
Abstract: Embodiments of the present disclosure are directed towards generating images conditioned on a desired attribute. In particular, an attribute-based image generation system can use a directional-GAN architecture to generate images conditioned on a desired attribute. A latent vector and a desired attribute are received. A feature subspace is determined for the latent vector using a latent-attribute linear classifier trained to determine a relationship between the latent vector and the desired attribute. An image is generated using the latent vector such that the image contains the desired attribute. In embodiments, where the feature space differs from a desired feature subspace, a directional vector is applied to the latent vector that shifts the latent vector from the feature subspace to the desired feature subspace. This modified latent vector is then used during generation of the image.
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30.发明申请公开(公告)号：US20210232478A1
公开(公告)日：2021-07-29
申请号：US16775815
申请日：2020-01-29
Applicant: Adobe Inc.
Inventor： Meghanath M Y , Shankar Venkitachalam , Deepak Pai
Abstract: In some embodiments, a computing system identifies a current engagement stage of a user with an online platform by applying a stage prediction model based on interaction data associated with the user. The interaction data describe actions performed by the user with respect to the online platform and context data associated with each of the actions. The computing system further identifies one or more critical events for promoting the user to transition from one engagement stage to a higher engagement stage based on the interaction data associated with the user. The computing system can make the identified current engagement stage of the user or the identified critical event to be accessible by the online platform so that user interfaces presented on the online platform can be modified to improve a likelihood of the user to transit from the current stage to a higher engagement stage.
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