| CPC G06Q 10/1053 (2013.01) | 18 Claims |
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1. A system of performing automated job recruitment, comprising:
a memory storing a machine learning model; and
a processor configured to execute the machine learning model, wherein the machine learning model is configured to:
initiate a common application configured to provide background information regarding a candidate;
identify a plurality of disparate types of background information for use in the common application;
incorporate the disparate types of background information into the common application;
dynamically update the common application in response to a change in a qualification of the candidate;
conduct a background check of the candidate based on the background information;
incorporate the background check into the common application, wherein the background check is incorporated into the common application in an embedded format with the common application;
providing access to the common application including the incorporated background check to a plurality of hiring entities having access to the common application;
receive a plurality of recruitment listings, wherein each recruitment listing includes data indicative of job qualifications;
compile a body of knowledge based on the received recruitment listings, wherein the body of knowledge includes information acquired from a plurality of disparate sources;
receive a job application from the candidate,
wherein the job application includes a resume and a target recruitment listing among the plurality of recruitment listings,
wherein the target recruitment listing indicates a specific job the candidate is applying to;
extract relevant data from the resume by analyzing the resume;
provide the job application of the candidate to a hiring entity, among the plurality of hiring entities, corresponding to the target recruitment listing prior to comparing the extracted relevant data from the resume with each recruitment listing in the body of knowledge other than the target recruitment listing;
upon providing the job application to the hiring entity corresponding to the target recruitment listing, provide the candidate with an automated status update response, indicating to the candidate that the candidate is being considered for the target recruitment listing, prior to comparing the extracted relevant data from the resume with each recruitment listing in the body of knowledge other than the target recruitment listing;
receive an acceptance/rejection communication from the hiring entity corresponding to the target recruitment listing, indicating whether the candidate has been accepted or rejected for the target recruitment listing;
when the acceptance/rejection communication indicates that the candidate has been accepted for the target recruitment listing:
provide the candidate with an automated acceptance update response, indicating to the candidate that the candidate has been accepted for the target recruitment listing;
provide the candidate with a request for approval to release the background check, in real-time, to the hiring entity corresponding to the target recruitment listing;
provide the hiring entity corresponding to the target recruitment listing, in real-time and via the common application, a digitally deliverable file including a link or a separately accessible computer file including the background check; and
when the acceptance/rejection communication indicates that the candidate has been rejected for the target recruitment listing:
provide the candidate with an automated rejection update response, indicating to the candidate that the candidate has been rejected for the target recruitment listing; and
compare the extracted relevant data from the resume with each recruitment listing in the body of knowledge other than the target recruitment listing,
wherein the memory stores computer instructions configured to instruct the processor to:
initially train the machine learning model on at least one first data set to dynamically update the common application with updated skills acquired by the candidate; and
iteratively retrain the machine learning model on at least one second and at least one third data set to dynamically update the common application with additional updated skills acquired by the candidate,
wherein iteratively retraining the machine learning model increases the accuracy of the machine learning model in identifying additional updated skills acquired by the candidate with respect to the initial training of the machine learning model,
wherein when the acceptance/rejection communication indicates that the candidate has been rejected for the target recruitment listing, the machine learning model is further configured to:
determine whether the candidate is a match with any one of the recruitment listings in the body of knowledge other than the target recruitment listing;
when it is determined that the candidate is a match with any one of the recruitment listings in the body of knowledge other than the target recruitment listing, provide the candidate with an automated matching update response, including information related to the matching recruitment listing; and
when it is determined that the candidate is not a match with any one of the recruitment listings in the body of knowledge other than the target recruitment listing, provide the candidate with an automated non-matching update response, indicating to the candidate that a match was not found.
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