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公开(公告)号：US20250123919A1
公开(公告)日：2025-04-17
申请号：US18484613
申请日：2023-10-11
Applicant: Intuit Inc.
Inventor： John SAMUEL , Sandeep MEWARA , Murari LAL
Abstract: Systems and methods for detecting errors in a data transfer uses a machine learning model to identify potential anomalies in the data transfer based on metadata. Mismatches between input data from the data transfer and output data after importing the data transfer may additionally be identified. User review and correction of data errors and potential anomalies identified using the machine learning model may be proactively prompted to ensure any errors or discrepancies are addressed before finalizing the import of the data transfer. User corrections are further used to retrain the machine learning model to enable continuous improvement and learning from the data transfer process.
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