Abstract: Apparatuses, systems, and methods described include receiving data related to an availability for a shift, automatically triggering initiation of a communications session related to the shift, conducting the communications session, and receiving and storing a plurality of audio or audio and visual signals from the communications session. Machine learning (ML) sentiment analysis is performed on data of the communications session and based on the sentiment analysis, a reliability score is determined.
Type:
Grant
Filed:
January 12, 2022
Date of Patent:
April 9, 2024
Assignee:
TRUEBLUE, INC.
Inventors:
Christopher A. Kapcar, Carlos A. Lara Maldonado, Robert Michael Ward, Jeffrey S Dirks
Abstract: 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.
Type:
Grant
Filed:
January 26, 2021
Date of Patent:
November 21, 2023
Assignee:
TRUEBLUE, INC.
Inventors:
Christopher A. Kapcar, Richard Paul Betori, Jeffrey Howard Rash, Robert Michael Ward, Jeffrey S. Dirks, Jeroen Anton Decker, Shawn David Dillenbeck
Abstract: 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.
Type:
Grant
Filed:
March 3, 2021
Date of Patent:
October 17, 2023
Assignee:
TrueBlue, Inc.
Inventors:
Christopher A. Kapcar, Richard Paul Betori, Jeffrey Howard Rash, Robert Michael Ward, Jeffrey S. Dirks, Jeroen Anton Decker, Shawn David Dillenbeck