Intuit, Inc.

Ruobing Lu

Ying Sun

Lei Pei

Nhung Ho

Juan Liu

Heather Simpson

Kishore Nene

Tarek Rabbani

Siddhartha Misra

A method utilizes a framework for transaction categorization personalization. A transaction record is received. a baseline model is selected from a plurality of machine learning models. An account identifier, corresponding to the transaction record using the baseline model, is selected. The account identifier for the transaction record is presented.

Framework for transaction categorization personalization

Certain aspects of the present disclosure provide techniques for improving a user experience based on electronic records of transactions. Embodiments include training a classifier using training data comprising a set of historical transaction descriptions and a set of corresponding historical classifications that indicate whether or not each historical transaction description of the set of historical transaction descriptions is associated with a user location. Embodiments further include receiving a transaction record describing a transaction associated with a user. Embodiments further include using the classifier to determine a classification for the transaction. The classification indicates whether or not the transaction description is associated with a location of the user. Embodiments further include providing, based at least in part on the classification, a communication to the user that relates to the location of the user.

Methods for identifying transactions with user location information

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Mountain View, CA, United States of America

Ruobing Lu