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公开(公告)号：US20240257100A1
公开(公告)日：2024-08-01
申请号：US18103867
申请日：2023-01-31
Applicant: American Express Travel Related Services Company, Inc , American Express Travel Related Services Company, Inc
CPC classification number: G06Q20/351 , G06Q20/20 , G06Q20/36 , G06Q20/3825
Abstract: Disclosed herein are system, method, and computer program product embodiments for providing a virtual card token to facilitate Real-Time Payment (RTP) network transactions. An account management system may facilitate RTP transactions with consumer bank accounts using the virtual card token. After providing the virtual card token to a user device, the user device may present the virtual card token to a merchant system to conduct a transaction. The virtual card token may operate with existing merchant systems and/or point-of-sale (POS) terminals. The merchant system may provide the virtual card token to the account management system for transaction approval. The account management system may select and retrieve funding from a particular bank account based on user-defined parameters. Upon retrieving funding from the particular bank account via the RTP network, the account management system may approve the transaction and/or provide payment to the merchant system.
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2.发明申请公开(公告)号：US20250070982A1
公开(公告)日：2025-02-27
申请号：US18456012
申请日：2023-08-25
Inventor： Mukund Shankar SimhaRaghu , Andras L. Ferenczi
Abstract: Disclosed are various approaches for issuing and verifying multi-claim verifiable credentials and verifiable presentations. In various embodiments, an issuer can send a request for information to a holder and obtain a response from the holder. The issuer can extract claims from the message, validate at least one of the claims, and generate a verifiable credential (VC) for the holder based at least in part on the claims, which can be sent to the holder. The holder can then generate a verifiable presentation (VP) based at least in part on the VC and send the VP to a verifier. The verifier can then verify the VP and interpret the claims within the VC.
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公开(公告)号：US12229114B2
公开(公告)日：2025-02-18
申请号：US17953390
申请日：2022-09-27
Applicant: American Express Travel Related Services Company, Inc. , American Express (India) Private Limited
Inventor： Vinay Dhingra , Agraj Gupta , Ashank Gupta , Vaibhav Gupta , Anam Hyderi , Sandeep Pattanayak , Purvi Shah , Shikha
Abstract: Disclosed are various embodiments for data anomaly detection. A variable profile is generated for each variable in source data. Then, the variable profiles are provided to each of a plurality of machine learning models. Next, it is determined, with each of the plurality of machine learning models, whether each variable profile is anomalous. The determination, from each of the plurality of machine learning models, whether each variable profile is anomalous is provided to an ensemble model. The ensemble model then generates a final determination whether each variable profile is anomalous. The final determination is then reported to an analysis service.
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公开(公告)号：US20250055691A1
公开(公告)日：2025-02-13
申请号：US18929558
申请日：2024-10-28
Inventor： Jile Gao , Maxwell Hardy , Terence Lee , Daniel J. Leonardis , Nimiksha Mahajan , Ely Marrero , Mohammad Naz , Oleksii Ozun , Julia Roytman , Brent Watson
Abstract: Disclosed are various embodiments for securely sharing confidential data between applications. A deep link request can be received from a first computing device, the deep link request identifying a set of data to be shared and a deep link schema. A token that represents the set of data can then be created. Also, a deep link that complies with the deep link schema and includes the token can also be created. The deep link and the token can then be returned to the first computing device. Later, a data request containing the token can be received from a second computing device. The set of data associated with the token can then be return to the second computing device.
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公开(公告)号：US12210836B2
公开(公告)日：2025-01-28
申请号：US18206296
申请日：2023-06-06
Inventor： Ravi Batra , Sandeep Bose , Mario Fragoso , Ravneet Ghuman , Madhu Sudan Reddy Gudur , Suraj Madnani , Curtis T. Merryweather , Ravi Varma , Vinod Yadav
Abstract: Systems and methods for identifying data of interest are disclosed. The system may retrieve unstructured data from an internet data source via an alert system or RSS feed. The system may input the unstructured data into various models and scoring systems to determine whether the data is of interest. The models and scoring systems may be executed in order or in parallel. For example, the system may input the unstructured data into a Naïve Bayes machine learning model, a long short-term memory (LSTM) machine learning model, a named entity recognition (NER) model, a semantic role labeling (SRL) model, a sentiment scoring algorithm, and/or a gradient boosted regression tree (GBRT) machine learning model. Based on determining that the unstructured data is of interest, a data alert may be generated and transmitted for manual review or as part of an automated decisioning process.
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Patent Agency Ranking
公开(公告)号：US20250021967A1
公开(公告)日：2025-01-16
申请号：US18220418
申请日：2023-07-11
Inventor： Andras L. Ferenczi
Abstract: Disclosed are various embodiments for using decentralized identity services and generative large language models (LLMs) to facilitate a humanized interactive chatbot session between two entities where information exchanged can be verified for accuracy. An interactive session can be established between a chat wallet service associated with a first user (e.g., a credential holder) and a second user (e.g., inquirer) using decentralized identity services. Inquiries asked by the second user can be directed to the chat wallet service which can obtain a response from a personalized dialog agent. The personalized dialog agent can obtain the answer by executing a language model that has been trained and personalized using information about the first user. The answer to the inquiry can be verified by comparing the answer with a verified credential associated with the first user. The verified response to the inquiry can then be provided to the second user.
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公开(公告)号：US20250005401A1
公开(公告)日：2025-01-02
申请号：US18884902
申请日：2024-09-13
Inventor： Venkatesh Nagarajan , Xiangzhen Kong , Neha Arya , Mansi Sharma
IPC: G06N5/04 , G06F16/9535 , G06N20/00
Abstract: At least some embodiments are directed to a prediction system of software objects. The prediction system predicts a first aspect of a user profile utilizing a categorization machine learning model and a user activity profile, the user profile and the user activity profile are associated with a user. The user activity profile comprises a plurality of values associated with demographics and historical activity data of the user. The prediction system predicts a software object associated with the user profile utilizing an optimization machine learning model, the first aspect of the user profile, and a second aspect of the user profile. The software object is optimized with respect to at least one competitive interest between the user associated with the user profile and an entity associated with the software object. The prediction system outputs the software object to a client computing device of the user.
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公开(公告)号：US12182784B2
公开(公告)日：2024-12-31
申请号：US18187289
申请日：2023-03-21
Inventor： David Alan Dillard , Ravikanth Erramilli , David Ibrahim , Barbara Lynn Shcolnik-Bateman , Sashidhar Karkada Srinivasa
Abstract: Transaction account holders are able to attach additional data to a transaction in concert with the transaction being initiated, prior to the merchant posting the transaction. Transaction account holders do not have to wait and/or opt for an external service provider to assist with the compiling and/or attaching of data at a later point in time (e.g., after the merchant posts the transaction). Transaction account holders may upload and access electronic receipts associated with a transaction authorization almost immediately after the sale and/or authorization of the transaction.
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公开(公告)号：US20240420176A1
公开(公告)日：2024-12-19
申请号：US18819978
申请日：2024-08-29
Inventor： Sastry V. Durvasula , Amit Prakash Gupta , Priyadarshini Koul , Premkumar Manivannan , Sathish Muthukrishnan , Harish R. Naik
IPC: G06Q30/0207 , A63F13/65 , A63F13/69 , A63F13/71 , A63F13/79 , G06Q30/0226 , G06Q30/0601
Abstract: A consumer may enroll in an event gamification system. An event listener may detect an event. The event gamification system may determine that the event qualifies for a game in which the consumer is enrolled. The event gamification system may transmit an achievement notification to the consumer as soon as the event occurs. The game may be displayed in a GUI on a consumer device. The consumer may be rewarded for completing the achievements in the game. Also, a server computer receiving a plurality of data sets that represent visually perceptible elements for a plurality of host web pages, wherein each of the plurality of host web pages displays an active link associated with a product on a merchant web page. The server automatically generating composite web page from: i) the particular data set associated with the particular host web page and the particular set of visually perceptible elements and ii) the related electronic content associated with the product from the merchant web page.
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公开(公告)号：US20240419911A1
公开(公告)日：2024-12-19
申请号：US18746937
申请日：2024-06-18
Inventor： Prodip HORE , Mrigank PRINCE , Jayatu Sen CHAUDHURY , Prakhar THAPAK , Soham BANERJEE , Shailja PANDEY , Chanderpreet Singh DUGGAL
IPC: G06F40/295 , G06F18/24 , G06N3/045
Abstract: At least some embodiments are directed to an entity classification system that receives informational data associated with an entity. The informational data includes sentences associated with the entity. The entity classification system utilizes a first machine learning model to determine a first contextual meaning among words of a sentence associated with the entity based on a first word embedding technique, and determines at least one category associated with the entity based at least in part on the first contextual meaning. The entity classification system utilizes a second machine learning model to determine a second contextual meaning shared by a set of sentences based on a second embedding technique, and determines a subcategory of the category associated with the entity based at least in part on the second contextual meaning. The entity classification system generates an output including the category and subcategory associated with the entity.
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