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公开(公告)号：US20250023911A1
公开(公告)日：2025-01-16
申请号：US18220440
申请日：2023-07-11
Applicant: Adobe Inc.
Inventor： Jan Kadel , Ritwik Sinha
Abstract: Techniques for web bot detection using behavioral analysis and machine learning are disclosed. In an example method, a processing device receives an indication of a network interaction by a client agent, from which behaviors of the client agent can be determined. A heuristics module may classify the client agent as in an unknown class based on the behaviors of the client agent. A trained adversarial neural network may also classify the client agent as in the unknown class. The processing device then generates a graph representation of the network interaction. A trained graph convolutional neural network may classify the client agent as in a bot class using the graph representation. Based on the classification of the client agent as a bot, the processing device executes a command to cause a bot countermeasure and generates a notification including information about the behaviors of the client agent.
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公开(公告)号：US12159482B2
公开(公告)日：2024-12-03
申请号：US17652026
申请日：2022-02-22
Applicant: ADOBE INC.
Inventor： Md Mehrab Tanjim , Ritwik Sinha , Moumita Sinha , David Thomas Arbour , Sridhar Mahadevan
IPC: G06V40/16
Abstract: Systems and methods for diversity auditing are described. The systems and methods include identifying a plurality of images; detecting a face in each of the plurality of images using a face detection network; classifying the face in each of the plurality of images based on a sensitive attribute using an image classification network; generating a distribution of the sensitive attribute in the plurality of images based on the classification; and computing a diversity score for the plurality of images based on the distribution.
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公开(公告)号：US20240152605A1
公开(公告)日：2024-05-09
申请号：US17983687
申请日：2022-11-09
Applicant: Adobe Inc.
Inventor： Xiang Chen , Yifu Zheng , Viswanathan Swaminathan , Sreekanth Reddy , Saayan Mitra , Ritwik Sinha , Niranjan Kumbi , Alan Lai
IPC: G06F21/55
CPC classification number: G06F21/554 , G06F2221/034
Abstract: In some embodiments, techniques for identifying email events generated by bot activity are provided. For example, a process may involve applying bot detection patterns to identify bot activity among email response events.
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公开(公告)号：US20240144307A1
公开(公告)日：2024-05-02
申请号：US18047421
申请日：2022-10-18
Applicant: ADOBE INC.
Inventor： Tung Mai , Ritwik Sinha , Trevor Hyrum Paulsen , Xiang Chen , William Brandon George , Nate Purser , Zhao Song
IPC: G06Q30/02
CPC classification number: G06Q30/0204
Abstract: One aspect of systems and methods for segment size estimation includes identifying a segment of users for a first time period based on time series data, wherein the time series data includes a series of interactions between users and a content channel and wherein the segment includes a portion of the users interacting with the content channel during the first time period; computing a segment return value for a second time period based on the time series data by computing a first subset and a second subset of the segment, wherein the first subset includes users that interact with the content channel greater than a threshold number of times during a range of the time series data and the second subset comprises a complement of the first subset with respect to the segment; and providing customized content to a user in the segment based on the segment return value.
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公开(公告)号：US20240046412A1
公开(公告)日：2024-02-08
申请号：US17880120
申请日：2022-08-03
Applicant: ADOBE INC.
Inventor： Md Mehrab Tanjim , Krishna Kumar Singh , Kushal Kafle , Ritwik Sinha
IPC: G06T3/40
CPC classification number: G06T3/4046 , G06T3/4053
Abstract: A system debiases image translation models to produce generated images that contain minority attributes. A balanced batch for a minority attribute is created by over-sampling images having the minority attribute from an image dataset. An image translation model is trained using images from the balanced batch by applying supervised contrastive loss to output of an encoder of the image translation model and an auxiliary classifier loss based on predicted attributes in images generated by a decoder of the image translation model. Once trained, the image translation model is used to generate images with the minority image when given an input image having the minority attribute.
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Patent Agency Ranking
公开(公告)号：US11790379B2
公开(公告)日：2023-10-17
申请号：US17004377
申请日：2020-08-27
Applicant: ADOBE INC.
Inventor： Shiv Kumar Saini , Ritwik Sinha , Moumita Sinha , David Arbour
IPC: G06Q30/0201 , G06Q30/0204 , H04N21/81 , G06Q30/0242 , H04L67/50 , G06N7/01
CPC classification number: G06Q30/0201 , G06N7/01 , G06Q30/0205 , G06Q30/0242 , H04L67/535 , H04N21/812
Abstract: A method, apparatus, and non-transitory computer readable medium for data analytics are described. Embodiments of the method, apparatus, and non-transitory computer readable medium include monitoring online activity corresponding to a plurality of users; receiving aggregate marketing data for a marketing activity; identifying online activity data for a time period corresponding to the marketing activity based on the monitoring; generating a regression model based on the aggregate marketing data and the online activity data using Bayesian regression, wherein the regression model represents a relationship between the marketing activity and the online activity, comprises a time effect coefficient, and is based on a prior distribution of the time effect coefficient that decays to zero as time increases; and estimating a treatment effect for the marketing activity on the online activity based on the regression model, wherein the treatment effect comprises a rate of effect decay.
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公开(公告)号：US11756058B2
公开(公告)日：2023-09-12
申请号：US17091569
申请日：2020-11-06
Applicant: ADOBE INC.
Inventor： Ritwik Sinha , Fan Du , Sunav Choudhary , Sanket Mehta , Harvineet Singh , Said Kobeissi , William Brandon George , Chris Challis , Prithvi Bhutani , John Bates , Ivan Andrus
IPC: G06Q30/00 , G06Q30/0201 , G06F17/18 , G06F16/904
CPC classification number: G06Q30/0201 , G06F16/904 , G06F17/18
Abstract: Determination of high value customer journey sequences is performed by determining customer interactions that are most frequent as length N=1 sub-sequences, recursively determining most frequent length N+1 sub-sequences that start with the length N sub-sequences, determining a first count indicating how often one of the sub-sequences appears in the sequences, determining a second count indicating how often the one sub-sequence resulted in the goal, and using the counts to determine the most or least effective sub-sequences for achieving the goal.
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公开(公告)号：US20230139824A1
公开(公告)日：2023-05-04
申请号：US17519311
申请日：2021-11-04
Applicant: ADOBE INC.
Inventor： Trisha Mittal , Viswanathan Swaminathan , Ritwik Sinha , Saayan Mitra , David Arbour , Somdeb Sarkhel
Abstract: Various disclosed embodiments are directed to using one or more algorithms or models to select a suitable or optimal variation, among multiple variations, of a given content item based on feedback. Such feedback guides the algorithm or model to arrive at suitable variation result such that the variation result is produced as the output for consumption by users. Further, various embodiments resolve tedious manual user input requirements and reduce computing resource consumption, among other things, as described in more detail below.
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公开(公告)号：US20220067753A1
公开(公告)日：2022-03-03
申请号：US17004377
申请日：2020-08-27
Applicant: ADOBE INC.
Inventor： SHIV KUMAR SAINI , Ritwik Sinha , Moumita Sinha , David Arbour
Abstract: A method, apparatus, and non-transitory computer readable medium for data analytics are described. Embodiments of the method, apparatus, and non-transitory computer readable medium include monitoring online activity corresponding to a plurality of users; receiving aggregate marketing data for a marketing activity; identifying online activity data for a time period corresponding to the marketing activity based on the monitoring; generating a regression model based on the aggregate marketing data and the online activity data using Bayesian regression, wherein the regression model represents a relationship between the marketing activity and the online activity, comprises a time effect coefficient, and is based on a prior distribution of the time effect coefficient that decays to zero as time increases; and estimating a treatment effect for the marketing activity on the online activity based on the regression model, wherein the treatment effect comprises a rate of effect decay.
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公开(公告)号：US11232483B2
公开(公告)日：2022-01-25
申请号：US16682089
申请日：2019-11-13
Applicant: ADOBE INC.
Inventor： Ritwik Sinha , David Arbour , Aahlad Manas Puli
Abstract: Systems and methods are described for a causal marketing attribution process that includes the receiving of a plurality of marketing events associated with a customer and computing a sum of a plurality of channel-specific terms corresponding to the plurality of marketing events, wherein each of the plurality of channel-specific terms comprises a channel-specific base parameter and a channel-specific decay parameter. Additionally, the causal marketing attribution process computes a sum of a plurality of interaction terms, wherein each interaction term comprises a product of a pair of channel-specific terms, and determines a probability of a target outcome for the customer based on the sum of the plurality of channel-specific terms and the sum of the plurality of interaction terms.
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