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:
May. 23, 2023

Filed:

Dec. 20, 2017
Applicant:

Visa International Service Association, San Francisco, CA (US);

Inventors:

Richa Garg, Mountain View, CA (US);

Walker Carlson, San Diego, CA (US);

Varun Sharma, Foster City, CA (US);

Nandakumar Kandaloo, Mountain View, CA (US);

Srijoy Aditya, Los Altos, CA (US);

Assignee:

Visa International Service Association, San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 30/0202 (2023.01); G06N 20/00 (2019.01); G06Q 10/04 (2023.01); G06Q 20/40 (2012.01); G06Q 30/0207 (2023.01); G06Q 30/0251 (2023.01); G06F 18/214 (2023.01);
U.S. Cl.
CPC ...
G06Q 30/0202 (2013.01); G06F 18/214 (2023.01); G06N 20/00 (2019.01); G06Q 10/04 (2013.01); G06Q 20/40 (2013.01); G06Q 30/0207 (2013.01); G06Q 30/0251 (2013.01);
Abstract

Described are a system, method, and computer program product for generating and applying a predictive wait time estimate using predictive modeling. The method includes receiving initial transaction data representative of a plurality of transactions between a plurality of transaction accounts and at least one merchant. The method also includes generating, for each subinterval, training data including at least one of the following: service rate during the subinterval, number of transactions during the subinterval, total transaction value during the subinterval, mean transaction value during the subinterval, year, month, day of week, or any combination thereof. The method further includes generating a predictive model that generates an output of arrival rate for an input of at least one time parameter. The method further includes generating the predictive wait time estimate for a designated time.


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