Invention Grant
- Patent Title: System, method, and computer program product for multi-domain ensemble learning based on multivariate time sequence data
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Application No.: US18268465Application Date: 2022-10-20
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Publication No.: US12118448B2Publication Date: 2024-10-15
- Inventor: Linyun He , Shubham Agrawal , Yu-San Lin , Yuhang Wu , Ishita Bindlish , Chiranjeet Chetia , Fei Wang
- Applicant: Visa International Service Association
- Applicant Address: US CA San Francisco
- Assignee: Visa International Service Association
- Current Assignee: Visa International Service Association
- Current Assignee Address: US CA San Francisco
- Agency: The Webb Law Firm
- International Application: PCT/US2022/047225 2022.10.20
- International Announcement: WO2023/069584A 2023.04.27
- Date entered country: 2023-06-20
- Main IPC: G06N20/20
- IPC: G06N20/20 ; G06N5/04

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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