Recommendation platform for skill development
Disclosed is a platform that manages worker users in a temporary staffing environment via an artificial machine learning model. The temporary staffing platform matches available workers to available shifts/gigs. Additional features include generating provisional or near-miss matches and informing workers how to turn those near-misses into full matches, plotting a gig-career path to develop additional skills, gamify development, and automatically generate resumes. The platform generates a set of skill tags associated with each shift/gig performed by the user. Designing of resume text files by the artificial machine learning model includes procedurally generated descriptions of experience the a user has based on the recording of each shift/gig performed by the user and the skill tags associated with each recorded shift/gig, wherein a format of the resume text file is formulated by the artificial machine learning model evaluating a mix of skill tags and employers amassed by the user.
1. A method for automatic document processing that generates a resume text file comprising:
executing, via a processor, an artificial machine learning model including a training data set of resumes, wherein the artificial machine learning model is biased toward resumes with one or more specific skills;
generating a set of skill tags associated with events that are posted on a temporary staffing application, wherein each of the set of skill tags indicates a skill employed by a given user during performance of a respective event, the temporary staffing application including a userbase that accepts and staffs the events, the userbase having profiles;
recording, in a first user profile of a first user, each event performed by the first user via the temporary staffing application including the set of skill tags and an employer associated with those events; and
automatically generating the resume text file for the first user, by filling fields of a resume template, the resume template specified by the artificial machine learning model evaluating a mix of skill tags and employers amassed by the first user and biased towards given skill tags that often occur together or employer and based on a direct relationship to a number of occurrences of the given skill tags or the employers in the first user profile, the resume text file includes procedurally generated descriptions of experience the first user has based on the recording of each event performed by the first user and the skill tags associated with each recorded event.
2. The method of claim 1 , wherein the artificial machine learning model uses as input, content of the first user profile, wherein skilled work is weighted as compared to unskilled work, as indicated by skill tags, in structuring the resume text file.
3. The method of claim 1 , further comprising:
in response to completion of a new event by the first user, updating the resume text file based on the skill tags associated with the new event performed by the first user.
4. The method of claim 1 , further comprising:
receiving user onboarding data from the first user while the first user is registering for the temporary staffing application, wherein the artificial machine learning model draws from the first user's user onboarding data to design the resume text file.
5. The method of claim 1 , further comprising:
receiving an indication that the first user has a first certification; and
wherein the artificial machine learning model includes a section in the resume text file associated with certifications, the section populated with at least the first certification.
6. The method of claim 1 , wherein said automatic generating of the resume text file is further based on reviews of the given user by a given employer associated with a given event.
7. A system of automatic document processing that generates a resume text file comprising:
a processor; and
a non-transitory computer-readable medium having stored thereon instructions that, when executed by the processor, cause the processor to perform operations including:
executing an artificial machine learning model including a training data set of resumes, wherein the artificial machine learning model is biased toward resumes with one or more specific skills;
generating a set of skill tags associated with events that are posted on a temporary staffing application, wherein each of the set of skill tags indicates a skill employed by a given user during performance of a respective event, the temporary staffing application including a userbase that accepts and staffs the events, the userbase having profiles;
recording, to a first user profile of a first user, each event performed by the first user via the temporary staffing application including the set of skill tags and an employer associated with those events; and
automatically generating the resume text file for the first user, la filling fields of a resume template, the resume template specified by the artificial machine learning model evaluating a mix of skill tags and employers amassed by the first user and biased towards given skill tags that often occur together or employer and based on a direct relationship to a number of occurrences of the given skill tags or the employers in the first user profile, the resume text file includes procedurally generated descriptions of experience the first user has based on the recording of each event performed by the first user and the skill tags associated with each recorded event.
8. The system of claim 7 , wherein the artificial machine learning model uses as input, content of the first user profile, wherein skilled work is weighted as compared to unskilled work, as indicated by skill tags, in structuring the resume text file.
9. The system of claim 7 , wherein the performed operations further include:
in response to completion of a new event by the first user, updating the resume text file based on the skill tags associated with the new event performed by the first user.
10. The system of claim 7 , wherein the performed operations further include:
receiving user onboarding data from the user while the user is registering for the temporary staffing application, wherein the artificial machine learning model draws from the user onboarding data to design the resume text file.
11. The system of claim 7 , wherein the performed operations further include:
receiving an indication that the first user has a first certification; and
wherein the artificial machine learning model includes a section in the resume text file associated with certifications, the section populated with at least the first certification.
12. The system of claim 7 , wherein said automatic generating of the resume text file is further based on reviews of the given user by a given employer associated with a given event.