US 11,676,053 B2
Systems, methods, and media for automatically identifying entrepreneurial individuals in a population using individual and population level data
Jonathan T. Eckhardt, Madison, WI (US); Bekhzod Khoshimov, Madison, WI (US); and Brent Goldfarb, Washington, DC (US)
Assigned to Wisconsin Alumni Research Foundation, Madison, WI (US); and University of Maryland, College Park, College Park, MD (US)
Filed by Wisconsin Alumni Research Foundation, Madison, WI (US); and University of Maryland, College Park, College Park, MD (US)
Filed on Apr. 15, 2022, as Appl. No. 17/721,582.
Application 17/721,582 is a continuation of application No. 16/404,597, filed on May 6, 2019, granted, now 11,308,411.
Claims priority of provisional application 62/667,367, filed on May 4, 2018.
Prior Publication US 2022/0245491 A1, Aug. 4, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 17/15 (2006.01); G06N 7/00 (2023.01); G06F 17/18 (2006.01); G06F 9/54 (2006.01)
CPC G06N 7/00 (2013.01) [G06F 17/15 (2013.01); G06F 17/18 (2013.01); G06F 9/541 (2013.01)] 11 Claims
OG exemplary drawing
 
7. A method for identifying entrepreneurial individuals associated with an application for venture funding, the method comprising:
receiving grade information associated with each of a plurality of individuals;
determining, for each of the plurality of individuals, a variation metric associated with the individual's grades;
identifying a plurality of institutions, each of the plurality of institutions associated with at least one of the plurality of individuals;
determining, for each institution associated with at least one individual, that an average variability metric associated with the institution is not stored in the memory;
identifying a first source of grade variability data for a first institution of the plurality of institutions, wherein the first institution is associated with a first individual of the plurality of individuals, the first individual associated with a first application for venture funding;
retrieving grade variability data for the first institution from the first source of grade variability data;
determining that the variation metric of the first individual's grades is larger than the average variation metric associated with the first institution by at least one standard deviation; and
causing information to be presented indicating that the first application for venture funding is associated with an individual that is more likely than average to be entrepreneurial.