US 12,282,899 B2
One click job placement
Stephen J. McHale, Chagrin Falls, OH (US); and Brian Lee Heath, Shaker Heights, OH (US)
Assigned to The Unify Project, Cleveland, OH (US)
Filed by The Unify Project, Cleveland, OH (US)
Filed on Oct. 20, 2021, as Appl. No. 17/506,232.
Application 17/506,232 is a continuation of application No. 17/220,576, filed on Apr. 1, 2021, granted, now 11,195,151.
Claims priority of provisional application 63/005,141, filed on Apr. 3, 2020.
Prior Publication US 2022/0036316 A1, Feb. 3, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 10/1053 (2023.01); G06Q 10/0631 (2023.01)
CPC G06Q 10/1053 (2013.01) [G06Q 10/063112 (2013.01)] 21 Claims
OG exemplary drawing
 
1. A computer implemented method of intelligent job matching, comprising:
executing, by at least one processor on a computer, a job matching algorithm implemented by an artificial intelligence (AI) system, stored on a non-transitory computer-readable memory medium that performs online job opening matching between a job-seeker profile and one or more job opening profiles, comprising the job matching algorithm performing the steps of:
retrieving from an applicant database, a first plurality of attributes in qualifications and a second plurality of attributes in characteristics of a job-seeker profile;
determining a weighted match score, by matching the corresponding first plurality of attributes in the qualifications between the job-seeker profile and the one or more job opening profiles retrieved from an employer database;
determining a weighted fit score, by matching the corresponding second plurality of attributes in the characteristics between the job-seeker profile and the one or more job opening profiles;
combining the weighted match score and the weighted fit score to determine an overall score;
training the AI system to continuously improve the job matching algorithm comprising a feedback loop implementing the following steps:
evaluating the overall score by comparing the overall score to a first threshold score;
when the evaluated overall score exceeds the first threshold score, establishing a successful match outcome for the one or more job opening profiles and when the overall threshold score is below the first threshold score, performing:
(a) adjusting the weighted match score and the weighted fit score to redetermine an adjusted overall score; and
(b) performing, according to the adjusted overall score, one or both of a re-matching to the one or more job opening profiles according to the first threshold score, and a new matching to a new job opening profile from the employer database, according to a second threshold score;
(c) reiteratively training the artificial intelligence (AI) system to perform the adjusting of the weighted match score and the adjusting of the weighted fit score for the re-matching to the one or more job opening profiles and the new matching to the new job opening profile to incrementally and continuously improve the job matching algorithm based on data from job-seeker behavior and actions; and
when a successful job opening re-matching or new job opening matching outcome is found by the trained AI system based on the adjusted overall score, advancing to the next recruitment or hiring decision, otherwise, continue to train the AI system by repeating the steps in (a) and (b) and (c) either until a successful job opening re-matching or new job opening matching or terminating after a defined number of repeated overall score adjusting, job opening re-matching or new job opening matching occurs; and
evaluating the job opening matching outcome based on both the feedback loop and implementing:
when the re-matching or the new matching is unsuccessful, inviting the job-seeker to consider other jobs and career paths based on matching to more job openings from the employer database under a curation criteria, over a defined range of the adjusted weighted match score and over a defined range of the adjusted weighted fit score.