US 12,021,644 B2
Computer-implemented systems configured for automated electronic calendar item predictions and methods of use thereof
James Zarakas, Centreville, VA (US); George Bergeron, Falls Church, VA (US); and Adam Vukich, Alexandria, VA (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Feb. 13, 2023, as Appl. No. 18/168,427.
Application 18/168,427 is a continuation of application No. 17/532,242, filed on Nov. 22, 2021, granted, now 11,582,050, issued on Feb. 14, 2023.
Application 17/532,242 is a continuation of application No. 16/872,003, filed on May 11, 2020, granted, now 11,184,183, issued on Nov. 23, 2021.
Application 16/872,003 is a continuation of application No. 16/748,529, filed on Jan. 21, 2020, granted, now 10,735,212, issued on Aug. 4, 2020.
Prior Publication US 2023/0275774 A1, Aug. 31, 2023
Int. Cl. H04L 12/18 (2006.01); G06N 20/00 (2019.01); G06Q 10/1093 (2023.01)
CPC H04L 12/1818 (2013.01) [G06N 20/00 (2019.01); G06Q 10/1095 (2013.01); H04L 12/1831 (2013.01)] 18 Claims
OG exemplary drawing
 
10. A system comprising:
at least one processor configured to implement software instructions causing the at least one processor to perform steps to:
receive an availability change notification from a first user;
wherein the availability change notification comprises an availability change time period associated with a change in availability of the first user;
identify at least one need-to-reschedule meeting data item of at least one need-to-reschedule meetings associated with the availability change time period;
wherein the at least one need-to-reschedule meeting data item identifies at least one additional user;
access meeting room availability data associated with at least one meeting room object for a subsequent time period;
wherein the at least one meeting room object comprises at least one data object indicative of at least one meeting room;
utilize a meeting scheduling machine learning model to predict a plurality of parameters of at least one meeting room object representing at least one candidate rescheduled meeting associated with the at least one need-to-reschedule meeting;
wherein the meeting scheduling machine learning model is configured to predict the plurality of parameters of the at least one meeting room object based at least in part on:
a meeting history data of the first user and the at least one additional user,
calendar data associated with the first user and the at least one additional user, and
the meeting room availability data associated with the at least one meeting room object; and
causing to display, by the at least one processor, an indication of at least one candidate rescheduled meeting and the at least one meeting room object in response to the at least one availability change notification on a screen of computing device associated with each user of the plurality of users.