	US 11,750,554 B2
	Computer-implemented systems configured for automated machine learning contact priority prediction for electronic messages and methods of use thereof
Adam Vukich, Alexandria, VA (US); George Bergeron, Falls Church, VA (US); and James Zarakas, Centreville, VA (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Aug. 22, 2022, as Appl. No. 17/892,935.
Application 17/892,935 is a continuation of application No. 17/323,497, filed on May 18, 2021, granted, now 11,425,080, issued on Aug. 23, 2022.
Application 17/323,497 is a continuation of application No. 16/863,721, filed on Apr. 30, 2020, granted, now 11,082,387, issued on Aug. 3, 2021.
Prior Publication US 2022/0400095 A1, Dec. 15, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. H04L 51/226 (2022.01); G06N 20/00 (2019.01); H04L 51/42 (2022.01); H04L 51/224 (2022.01)

CPC H04L 51/226 (2022.05) [G06N 20/00 (2019.01); H04L 51/224 (2022.05); H04L 51/42 (2022.05)]

20 Claims

1. A method comprising:

rendering, by at least one processor, an electronic messaging interface of an electronic messaging software application;

wherein the electronic messaging software application is configured to receive a plurality of electronic messages;

wherein the plurality of electronic messages is associated with at least one sender and an electronic message text;

wherein the electronic messaging interface comprises a prioritized electronic message list that displays the plurality of electronic messages in an order according to a current prioritized ordering of the plurality of electronic messages;

wherein the electronic messaging software application is configured to dynamically update the current prioritized ordering of the plurality of electronic messages by:

accessing, by the at least one processor, a plurality of collaboration data objects residing in at least one collaboration database;

wherein the plurality of collaboration data objects are associated with at least one user and at least one collaboration text;

wherein the plurality of collaboration data objects comprises at least one of:

at least one electronic work task object,

at least one additional electronic message, or

at least one personnel data record associated with the at least one user;

determining, by the at least one processor, at least one collaboration data object of the plurality of collaboration data objects associated with at least one electronic message of the plurality of electronic messages based at least in part on a matching of:

the at least one sender with the at least one user, and

the electronic message text with the at least one collaboration text;

utilizing, by the at least one processor, a message prioritization machine learning model to predict an updated prioritized ordering of the plurality of electronic messages based at least in part on at least one parameter associated with each of the plurality of electronic messages;

wherein the at least one parameter comprises at least one collaboration data object parameter that represents the at least one collaboration data object associated with a respective electronic message,

wherein the updated prioritized ordering comprises an order of notification of each electronic message of the at least one electronic message according to a message priority of each electronic message at a current time; and

updating, by the at least one processor, the electronic messaging interface to update the prioritized electronic message list according to the updated prioritized ordering.