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1.发明申请
公开(公告)号：WO2023069244A1
公开(公告)日：2023-04-27
申请号：PCT/US2022/045337
申请日：2022-09-30
Applicant: VISA INTERNATIONAL SERVICE ASSOCIATION
Inventor： CHEN, Huiyuan , LIN, Yu-San , PAN, Menghai , WANG, Lan , YEH, Michael , WANG, Fei , YANG, Hao
IPC: G06N3/02
Abstract: Described are a system, method, and computer program product for denoising sequential machine learning models. The method includes receiving data associated with a plurality of sequences and training a sequential machine learning model based on the data associated with the plurality of sequences to produce a trained sequential machine learning model. Training the sequential machine learning model includes denoising a plurality of sequential dependencies between items in the plurality of sequences using at least one trainable binary mask. The method also includes generating an output of the trained sequential machine learning model based on the denoised sequential dependencies. The method further includes generating a prediction of an item associated with a sequence of items based on the output of the trained sequential machine learning model.
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2.发明申请
公开(公告)号：WO2023069584A1
公开(公告)日：2023-04-27
申请号：PCT/US2022/047225
申请日：2022-10-20
Applicant: VISA INTERNATIONAL SERVICE ASSOCIATION
Inventor： HE, Linyun , AGRAWAL, Shubham , LIN, Yu-San , WU, Yuhang , BINDLISH, Ishita , CHETIA, Chiranjeet , WANG, Fei
Abstract: Systems, methods, and computer program products for multi-domain ensemble learning based on multivariate time sequence data are provided. A method may include receiving multivariate sequence data. At least a portion of the multivariate sequence data may be inputted into a plurality of anomaly detection models to generate a plurality of scores. The multivariate sequence data may be combined with the plurality of scores to generate combined intermediate data. The combined intermediate data may be inputted into a combined ensemble model to generate an output score. In response to determining that the output score satisfies a threshold, at least one of an alert may be communicated to a user device, the multivariate sequence data may be inputted into the feature-domain ensemble model to generate a feature importance vector, or at least one of a model-domain, a time-domain, a feature-domain, or the combined ensemble model may be updated.
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3.发明申请
公开(公告)号：WO2022082091A1
公开(公告)日：2022-04-21
申请号：PCT/US2021/055374
申请日：2021-10-18
Applicant: VISA INTERNATIONAL SERVICE ASSOCIATION
Inventor： DONG, Bo , WU, Yuhang , LIN, Yu-San , YEH, Michael , YANG, Hao
IPC: G08B23/00
Abstract: Described are a system, method, and computer program product for user network activity anomaly detection. The method includes receiving network resource data associated with network resource activity of a plurality of users and generating a plurality of layers of a multilayer graph from the network resource data. Each layer of the plurality of layers may include a plurality of nodes, which are associated with users, connected by a plurality of edges, which are representative of node interdependency. The method also includes generating a plurality of adjacency matrices from the plurality of layers and generating a merged single layer graph based on a weighted sum of the plurality of adjacency matrices. The method further includes generating anomaly scores for each node in the merged single layer graph and determining a set of anomalous users based on the anomaly scores.
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公开(公告)号：WO2022231647A1
公开(公告)日：2022-11-03
申请号：PCT/US2021/051686
申请日：2021-09-23
Applicant: VISA INTERNATIONAL SERVICE ASSOCIATION
Inventor： CHEN, Huiyuan , LIN, Yu-San , WANG, Fei , YANG, Hao
Abstract: A method includes determining a set of regions for each of a first plurality of images of a first item type, a second plurality of images of a second item type, and a third plurality of images of a third item type. The method also includes for each region in each set of regions of the images, generating, by the processing computer, a vector representing the region, and then generating a plurality of aggregated messages using the vectors corresponding to combinations of images of different types of items, the images being from the first, second, and third plurality of images. Then, unified embeddings are generated for the images in the first, second, and third plurality of images, respectively, using aggregated messages in the plurality of aggregated messages. Matching scores associated with combinations of the images are created using the unified embeddings and a machine learning model.
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Patent Agency Ranking5.发明申请
公开(公告)号：WO2020046789A1
公开(公告)日：2020-03-05
申请号：PCT/US2019/048094
申请日：2019-08-26
Applicant: VISA INTERNATIONAL SERVICE ASSOCIATION
Inventor： MOOSAEI, Maryam , LIN, Yu-San , YANG, Hao
Abstract: Systems, methods, and computer program products for predicting user preference of items in an image process image data associated with a single image with a first branch of a neural network to produce an image embedding, the single image including a set of multiple items; process a user identifier of a user with a second branch of the neural network to produce a user embedding; concatenate the image embedding with the user embedding to produce a concatenated embedding; process the concatenated embedding with the neural network to produce a joint embedding; and generate a user preference score for the set of multiple items from the neural network based on the joint embedding, the user preference score including a prediction of whether the user prefers the set of multiple items.
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公开(公告)号：WO2023014567A1
公开(公告)日：2023-02-09
申请号：PCT/US2022/038630
申请日：2022-07-28
Applicant: VISA INTERNATIONAL SERVICE ASSOCIATION
Inventor： WANG, Fei , CAI, Yiwei , WANG, Lan , LIN, Yu-San , WU, Yuhang , WANG, Sheng , CHEN, Qingguo
Abstract: Provided is a system, method, and computer program product for a framework for monitoring acquirer credit settlement risk. A system for monitoring acquirer credit settlement risk includes a transaction database and at least one processor. The processor may be programmed or configured to generate a first acquirer risk score based on a plurality of transaction records and a first risk algorithm, a first merchant risk score based on the plurality of transaction records and the first risk algorithm, a second acquirer risk score based on the plurality of transaction records and a second risk algorithm, and a second merchant risk score based on the plurality of transaction records and the second risk algorithm. A final acquirer risk score may be generated based on the first acquirer risk score, the second acquirer risk score, the first merchant risk score, and the second merchant risk score.
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公开(公告)号：WO2022261447A1
公开(公告)日：2022-12-15
申请号：PCT/US2022/033022
申请日：2022-06-10
Applicant: VISA INTERNATIONAL SERVICE ASSOCIATION
Inventor： LIN, Yu-San , WANG, Lan , WU, Yuhang , CHEN, Huiyuan , WANG, Fei , YANG, Hao
Abstract: A computer obtains node embeddings, node periodicity classifications, edge embeddings, and edge periodicity classifications for each time of a time period. The computer determines subgraph embeddings based on a subgraph of the graph, times in the time period, the node embeddings for nodes in the subgraph, the edge embeddings for edges in the subgraph, the node periodicity classifications for the nodes in the subgraph, and the edge periodicity classifications for the edges in the subgraph. The computer translates each subgraph embedding of the subgraph embeddings for each time of the time period into projected subgraph embeddings. For the subgraph, the computer aggregates the plurality of projected subgraph embeddings into an aggregated subgraph embedding. The computer determines if the subgraph is periodic based upon at least the aggregated subgraph embedding.
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8.发明申请
公开(公告)号：WO2022261420A1
公开(公告)日：2022-12-15
申请号：PCT/US2022/032984
申请日：2022-06-10
Applicant: VISA INTERNATIONAL SERVICE ASSOCIATION
Inventor： WANG, Lan , LIN, Yu-San , WU, Yuhang , CHEN, Huiyuan , WANG, Fei , YANG, Hao
Abstract: Provided is a system for detecting an anomaly in a multivariate time series that includes at least one processor programmed or configured to receive a dataset of a plurality of data instances, wherein each data instance comprises a time series of data points, determine a set of target data instances based on the dataset, determine a set of historical data instances based on the dataset, generate, based on the set of target data instances, a true value matrix, a true frequency matrix, and a true correlation matrix, generate a forecast value matrix, a forecast frequency matrix, and a forecast correlation matrix based on the set of target data instances and the set of historical data instances, determine an amount of forecasting error, and determine whether the amount of forecasting error corresponds to an anomalous event associated with the dataset of data instances. Methods and computer program products are also provided.
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公开(公告)号：WO2022169480A1
公开(公告)日：2022-08-11
申请号：PCT/US2021/040312
申请日：2021-07-02
Applicant: VISA INTERNATIONAL SERVICE ASSOCIATION
Inventor： CHEN, Huiyuan , LIN, Yu-San , WANG, Lan , YEH, Michael , WANG, Fei , YANG, Hao
Abstract: A method includes receiving a first data set comprising embeddings of first and second types, generating a fixed adjacency matrix from the first dataset, and applying a first stochastic binary mask to the fixed adjacency matrix to obtain a first subgraph of the fixed adjacency matrix. The method also includes processing the first subgraph through a first layer of a graph convolutional network (GCN) to obtain a first embedding matrix, and applying a second stochastic binary mask to the fixed adjacency matrix to obtain a second subgraph of the fixed adjacency matrix. The method includes processing the first embedding matrix and the second subgraph through a second layer of the GCN to obtain a second embedding matrix, and then determining a plurality of gradients of a loss function, and modifying the first stochastic binary mask and the second stochastic binary mask using at least one of the plurality of gradients.
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