IP Library Granted Patent US 12,236,367
Granted Patent B2
US 12,236,367 · App. 18/409,987 · Granted Feb 25, 2025

Method and system for smart detection of business hot spots

Inventors: Grace Wu (Mountain View, CA); Shashank Shashikant Rao (San Jose, CA); Susrutha Gongalla (Mountain View, CA); Nhung Ho (Redwood City, CA); Carly Wood (Mountain View, CA); Vaibhav Sharma (Mountain View, CA)
Assignee: Intuit Inc.
G06N5/048G06Q10/04
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Quick Facts
Patent No.
US 12,236,367
App. No.
18/409,987
Granted
Feb 25, 2025
Kind
B2
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.

Claims (82)

1. A method for trip classification, comprising:

receiving, from a plurality of users, a plurality of classified trip records, wherein each classified trip record of the plurality of classified trip records comprises:

one or more trip attributes comprising an attribute associated with a respective user of the plurality of users; and

classification information;

determining a hot spot based on the plurality of classified trip records received from the plurality of users, wherein the hot spot comprises a region that encompasses one or more locations; and

storing an association between the hot spot, a corresponding attribute related to one or more respective users of the plurality of users, and corresponding classification information;

receiving a trip record comprising a location related to a trip and a given attribute associated with a user related to the trip; and

predicting a classification of business or personal for the trip based on:

the location related to the trip;

the given attribute associated with the user related to the trip; and

the association between the hot spot, the corresponding attribute related to the one or more respective users of the plurality of users-, and the corresponding classification information.

2. The method of claim 1 , wherein each classified trip record of the classified trip records comprises one or more of:

an origin location; or

a destination location.

3. The method of claim 1 , wherein the hot spot comprises a dynamic region.

4. The method of claim 1 , wherein the location related to the trip comprises:

an origin location; or

a destination location.

5. The method of claim 1 , wherein predicting the classification for the trip comprises determining that the location related to the trip falls within the hot spot.

6. The method of claim 1 , further comprising providing the classification to a user.

7. The method of claim 6 , further comprising:

receiving feedback from the user about the classification; and

predicting one or more classifications of subsequent trip records based in part on the feedback.

8. The method of claim 1 , wherein predicting the classification for the trip is based on:

one or more classified trip records of a user associated with the trip record; and

one or more additional classified trip records of one or more users other than the user.

9. The method of claim 1 , wherein the given attribute associated with the user related to the trip comprises one or more of:

an occupation of the user related to the trip;

an industry of the user related to the trip;

an income of the user related to the trip;

a spending habit of the user related to the trip;

an address of the user related to the trip; or

an education of the user related to the trip.

10. A system for trip classification, the system comprising:

one or more processors; and

memory comprising instructions that, when executed by the one or more processors, cause the system to:

receive, from a plurality of users, a plurality of classified trip records, wherein each classified trip record of the plurality of classified trip records comprises:

one or more trip attributes comprising an attribute associated with a respective user of the plurality of users; and

classification information;

determine a hot spot based on the plurality of classified trip records received from the plurality of users, wherein the hot spot comprises a region that encompasses one or more locations; and

store an association between the hot spot, a corresponding attribute related to one or more respective users of the plurality of users, and corresponding classification information;

receive a trip record comprising a location related to a trip and a given attribute associated with a user related to the trip; and

predict a classification of business or personal for the trip based on:

the location related to the trip;

the given attribute associated with the user related to the trip; and

the association between the hot spot, the corresponding attribute related to the one or more respective users of the plurality of users, and the corresponding classification information.

11. The system of claim 10 , wherein each classified trip record of the classified trip records comprises one or more of:

an origin location; or

a destination location.

12. The system of claim 10 , wherein the hot spot comprises a dynamic region.

13. The system of claim 10 , wherein the location related to the trip comprises:

an origin location; or

a destination location.

14. The system of claim 10 , wherein predicting the classification for the trip comprises determining that the location related to the trip falls within the hot spot.

15. The system of claim 10 , wherein the instructions, when executed by the one or more processors, further cause the system to provide the classification to a user.

16. The system of claim 15 , wherein the instructions, when executed by the one or more processors, further cause the system to:

receive feedback from the user about the classification; and

predict one or more classifications of subsequent trip records based in part on the feedback.

17. The system of claim 10 , wherein predicting the classification for the trip is based on:

one or more classified trip records of a user associated with the trip record; and

one or more additional classified trip records of one or more users other than the user.

18. The system of claim 10 , wherein the given attribute associated with the user related to the trip comprises one or more of:

an occupation of the user related to the trip;

an industry of the user related to the trip;

an income of the user related to the trip;

a spending habit of the user related to the trip;

an address of the user related to the trip; or

an education of the user related to the trip.

19. A non-transitory computer-readable medium comprising instructions that, when executed by one or more processors of a computing system, cause the computing system to:

receive, from a plurality of users, a plurality of classified trip records, wherein each classified trip record of the plurality of classified trip records comprises:

one or more trip attributes comprising an attribute associated with a respective user of the plurality of users; and

classification information;

determine a hot spot based on the plurality of classified trip records received from the plurality of users, wherein the hot spot comprises a region that encompasses one or more locations; and

store an association between the hot spot, a corresponding attribute related to one or more respective users of the plurality of users, and corresponding classification information;

receive a trip record comprising a location related to a trip and a given attribute associated with a user related to the trip; and

predict a classification of business or personal for the trip based on:

the location related to the trip;

the given attribute associated with the user related to the trip; and

the association between the hot spot, the corresponding attribute related to the one or more respective users of the plurality of users-, and the corresponding classification information.

20. The non-transitory computer-readable medium of claim 19 , wherein each classified trip record of the classified trip records comprises one or more of:

an origin location; or

a destination location.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 11, 2024
From: WU, GRACE; SHASHIKANT RAO, SHASHANK; GONGALLA, SUSRUTHA; HO, NHUNG; WOOD, CARLY; SHARMA, VAIBHAV
To: INTUIT, INC.
Reel/Frame 066096/0343 →
Continuity (4)
Continuation 18194679 · Apr 3, 2023
Continuation 17404356 · Aug 17, 2021
Continuation 15913812 · Mar 6, 2018
Related Publication 20240144059A1 · May 2, 2024
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