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    Feature subspace isolation and disentanglement in merchant embeddings
    2.
    发明授权
    Feature subspace isolation and disentanglement in merchant embeddings 有权

    公开(公告)号：US12002052B2

    公开(公告)日：2024-06-04

    申请号：US16596665

    申请日：2019-10-08

    Applicant: Visa International Service Association

    Inventor： Sunipa Dev ,  Yan Zheng ,  Wei Zhang

    IPC: G06F17/16 ,  G06Q20/40 ,  G06Q50/12

    CPC classification number: G06Q20/4015 ,  G06F17/16 ,  G06Q50/12

    Abstract: A computer-implemented method for providing merchant recommendations comprises receiving, by a processor, raw merchant embeddings generated from payment transaction records, wherein the raw merchant embeddings include a plurality of embedded features entangled in an embedding space. The processor uses transaction metadata associated with the payment transaction records to determine a subspace of an identified feature within the embedding space. A linear transformation process then removes the subspace of the identified feature from the embedding space to create modified merchant embeddings that are merged and aligned with other ones of the plurality of features within the embedding space. The processor automatically generates a list of merchant rankings based on the modified merchant embeddings, past preferences of a target user using raw user embeddings, and a target region, and provides the list of merchant rankings to the target user.

    System, Method, and Computer Program Product for Saving Memory During Training of Knowledge Graph Neural Networks
    4.
    发明申请
    System, Method, and Computer Program Product for Saving Memory During Training of Knowledge Graph Neural Networks 有权

    公开(公告)号：US20250111213A1

    公开(公告)日：2025-04-03

    申请号：US18844254

    申请日：2023-05-01

    Applicant: Visa International Service Association

    Inventor： Huiyuan Chen ,  Xiaoting Li ,  Michael Yeh ,  Yan Zheng ,  Hao Yang

    IPC: G06N3/0495 ,  G06N3/084

    Abstract: Systems, methods, and computer program products are provided for saving memory during training of knowledge graph neural networks. The method includes receiving a training dataset including a first set of knowledge graph embeddings associated with a plurality of entities for a first layer of a knowledge graph, inputting the training dataset into a knowledge graph neural network to generate at least one further set of knowledge graph embeddings associated with the plurality of entities for at least one further layer of the knowledge graph, quantizing the at least one further set of knowledge graph embeddings to provide at least one set of quantized knowledge graph embeddings, storing the at least one set of quantized knowledge graph embeddings in a memory, and dequantizing the at least one set of quantized knowledge graph embeddings to provide at least one set of dequantized knowledge graph embeddings.

    Unsupervised embeddings disentanglement using a gan for merchant recommendations
    5.
    发明授权
    Unsupervised embeddings disentanglement using a gan for merchant recommendations 有权

    公开(公告)号：US12175504B2

    公开(公告)日：2024-12-24

    申请号：US18085034

    申请日：2022-12-20

    Applicant: Visa International Service Association

    Inventor： Yan Zheng ,  Yuwei Wang ,  Wei Zhang ,  Michael Yeh ,  Liang Wang

    IPC: G06Q30/00 ,  G06Q30/0201 ,  G06Q30/0282

    Abstract: Embodiments for training a recommendation system to provide merchant recommendations comprise receiving, by a processor, raw merchant embeddings and raw user embeddings generated from payment transaction records, wherein the raw merchant embeddings include a plurality of embedded features. A generative adversarial network (GAN) is trained to generate modified merchant embeddings from the raw merchant embeddings, where the modified embeddings remove a location feature. Subsequent to training and responsive to receiving a request for merchant recommendations in the target location for the target user, the GAN and a trained preference model are used to generate a list of merchant rankings based on a new set of modified merchant embeddings, past preferences of a target user, and the target location to recommend merchants in the target location.

    Method and system for assessing the reputation of a merchant
    9.
    发明授权
    Method and system for assessing the reputation of a merchant 有权

    公开(公告)号：US12141807B2

    公开(公告)日：2024-11-12

    申请号：US17763255

    申请日：2019-10-31

    Applicant: VISA INTERNATIONAL SERVICE ASSOCIATION

    Inventor： Liang Wang ,  Dhruv Gelda ,  Robert Christensen ,  Wei Zhang ,  Hao Yang ,  Yan Zheng

    IPC: G06Q20/40 ,  G06Q30/018

    Abstract: The system and method may assess the merchant risk level on a more continuous scale rather than a binary categorization. It may produce a continuous risk score proportional to the likelihood of a merchant being risky, effectively addressing the issue of shades of gray encountered by the traditional blacklisting approach. The continuous risk score feature provides greater flexibility as it allows the payment network to make dynamic pricing decisions (known as interchange optimization) based on the merchant risk level. Using collective intelligence from transactions across the payment network, the system and method may be able to assess the merchant risk level with high accuracy. The system and method may be particularly beneficial to small merchants with low transaction volume as even a few fraudulent transactions can easily put them in the high-risk merchant category. Further, the system and method may help payment processing networks make better decision on cross-border transactions.

    ERROR-BOUNDED APPROXIMATE TIME SERIES JOIN USING COMPACT DICTIONARY REPRESENTATION OF TIME SERIES
    10.
    发明公开
    ERROR-BOUNDED APPROXIMATE TIME SERIES JOIN USING COMPACT DICTIONARY REPRESENTATION OF TIME SERIES 审中-公开

    公开(公告)号：US20240273095A1

    公开(公告)日：2024-08-15

    申请号：US18567717

    申请日：2022-06-01

    Applicant: Visa International Service Association

    Inventor： Michael Yeh ,  Yan Zheng ,  Junpeng Wang ,  Wei Zhang ,  Zhongfang Zhuang

    IPC: G06F16/2453 ,  G06F16/2458

    CPC classification number: G06F16/24537 ,  G06F16/2465 ,  G06F16/2477

    Abstract: A method is disclosed. The method comprises determining a time series, a subsequence length. The length of the time series may then be determined, and an initial matrix profile may then be computed. The method may then form a processed matrix profile for a first subsequence of the subsequence length by applying the first subsequence to the initial matrix profile. A second subsequence may then be determined from the processed matrix profile. The method may then include comparing the second subsequence to other subsequences in a dictionary and adding it to the dictionary. The subsequences in the dictionary may be used to generate a plurality of subsequence matrix profiles. The method may then include forming an approximate matrix profile using the plurality of subsequence matrix profiles and then determining one or more anomalies in the time series or another time series using the approximate matrix profile.

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