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公开(公告)号：US11822881B1
公开(公告)日：2023-11-21
申请号：US17159015
申请日：2021-01-26
申请人： TrueBlue, Inc.
发明人： Christopher A. Kapcar , Richard Paul Betori , Jeffrey Howard Rash , Robert Michael Ward , Jeffrey S. Dirks , Jeroen Anton Decker , Shawn David Dillenbeck
IPC分类号： G06F40/186 , G06N20/00 , G06F40/174
CPC分类号： G06F40/186 , G06F40/174 , G06N20/00
摘要： 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.
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公开(公告)号：US20230019856A1
公开(公告)日：2023-01-19
申请号：US17379708
申请日：2021-07-19
申请人： TrueBlue, Inc.
摘要： Disclosed is a platform that manages worker users in a temporary staffing environment via an AI machine learning model. The machine learning model predicts dispatch outcomes of a plurality of pairings of worker users to potential shifts. A dispatch outcome predicts whether a worker will show up for and work a given shift. The machine learning model is based on a set of training data surrounding historical dispatch outcomes. The data surrounding the historical dispatch outcomes includes data relating to users, data relating to shifts, and data derived from a combination of both. An implementation of the machine learning model stitches together multiple shifts for up to a schedule horizon based on predicted dispatch outcomes.
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公开(公告)号：US12112126B2
公开(公告)日：2024-10-08
申请号：US18461778
申请日：2023-09-06
申请人： TrueBlue, Inc.
发明人： Christopher A. Kapcar , Richard Paul Betori , Jeffrey Howard Rash , Robert Michael Ward , Jeffrey S. Dirks , Jeroen Anton Decker , Shawn David Dillenbeck
IPC分类号： G06F40/186 , G06F40/174 , G06N20/00
CPC分类号： G06F40/186 , G06F40/174 , G06N20/00
摘要： 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.
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4.发明授权公开(公告)号：US11954619B1
公开(公告)日：2024-04-09
申请号：US17574532
申请日：2022-01-12
申请人： TrueBlue, Inc.
IPC分类号： G06Q10/0631 , G06N5/04
CPC分类号： G06Q10/063112 , G06N5/04 , G06Q10/06312
摘要： 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.
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公开(公告)号：US11989504B2
公开(公告)日：2024-05-21
申请号：US17191076
申请日：2021-03-03
申请人： TrueBlue, Inc.
发明人： Christopher A. Kapcar , Richard Paul Betori , Jeffrey Howard Rash , Robert Michael Ward , Jeffrey S. Dirks , Jeroen Anton Decker , Shawn David Dillenbeck
IPC分类号： G06F40/186 , G06F40/174 , G06N20/00
CPC分类号： G06F40/186 , G06F40/174 , G06N20/00
摘要： 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.
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公开(公告)号：US11790163B2
公开(公告)日：2023-10-17
申请号：US17191047
申请日：2021-03-03
申请人： TrueBlue, Inc.
发明人： Christopher A. Kapcar , Richard Paul Betori , Jeffrey Howard Rash , Robert Michael Ward , Jeffrey S. Dirks , Jeroen Anton Decker , Shawn David Dillenbeck
IPC分类号： G06F40/186 , G06N20/00 , G06F40/174
CPC分类号： G06F40/186 , G06F40/174 , G06N20/00
摘要： 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.
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公开(公告)号：US20230101734A1
公开(公告)日：2023-03-30
申请号：US17934539
申请日：2022-09-22
申请人： TrueBlue, Inc.
摘要： Disclosed is a platform that makes use of hybrid model employing both heuristic and machine learning models to adaptively generate recommendations based on requested circumstances in a temporary staffing platform. The hybrid model is based on a set of training data surrounding historical temporary staffing outcomes. The heuristic model portion identifies matches between current queries to past outcomes and the machine learning model portion trains to derive new recommendations where no match exists. Queries are received and executed upon in real-time as opposed to pre-computing based on the frequency of changes to the recommendation to what would otherwise be the same query. The hybrid model is therefore configured to optimize for real-time responses to individual queries. The data surrounding the historical temporary staffing outcomes includes data relating to users, data relating to shifts, and data derived from a combination of both.
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