The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Feb. 25, 2025

Filed:

Jan. 11, 2024
Applicant:

Intuit Inc., Mountain View, CA (US);

Inventors:

Grace Wu, Mountain View, CA (US);

Shashank Shashikant Rao, San Jose, CA (US);

Susrutha Gongalla, Mountain View, CA (US);

Nhung Ho, Redwood City, CA (US);

Carly Wood, Mountain View, CA (US);

Vaibhav Sharma, Mountain View, CA (US);

Assignee:

Intuit Inc., Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 5/048 (2023.01); G06Q 10/04 (2023.01);
U.S. Cl.
CPC ...
G06N 5/048 (2013.01); G06Q 10/04 (2013.01);
Abstract

Aspects of the present disclosure provide techniques for classifying a trip. Embodiments include receiving, from a plurality of users, a plurality of historical trip records. Each of the plurality of historical trip records may comprise one or more historical trip attributes and historical classification information. Embodiments include training a predictive model, using the plurality of historical trip records, to classify trips based on trip records. Training the predictive model may comprise determining a plurality of hot spots based on the historical trip records, each of the plurality of hot spots comprising a region encompassing one or more locations, and associating, in the predictive model, the plurality of hot spots with historical classification information. Embodiments include receiving, from a user, a new trip record comprising a plurality of trip attributes related to a trip and using the predictive model to predict a classification for the trip based on the trip record.


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