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US Patent 11861518 High fidelity predictions of service ticket escalation

Patent 11861518 was granted and assigned to SupportLogic on January, 2024 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent
0

Patent attributes

Patent Applicant
SupportLogic
SupportLogic
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Current Assignee
SupportLogic
SupportLogic
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
118615180
Patent Inventor Names
Zach Riddle0
Poonam Rath0
Andrew Langdon0
Lawrence Spracklen0
Charles Monnett0
Date of Patent
January 2, 2024
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Patent Application Number
169149350
Date Filed
June 29, 2020
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Patent Citations
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US Patent 10498904 Automated telephone host system interaction
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US Patent 10887462 System and method for assisting an agent during a client interaction
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US Patent 9000934 Apparatus, method, and system for determining end-of-life of a product
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US Patent 9229800 Problem inference from support tickets
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US Patent 9473637 Learning generation templates from dialog transcripts
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US Patent 9678817 Lifespan forecast for storage media devices
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US Patent 10438212 Ensemble machine learning based predicting customer tickets escalation
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Patent Citations Received
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US Patent 12093640 Optimizing questions to retain engagement
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Patent Primary Examiner
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Crystol Stewart
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CPC Code
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G06Q 10/06375
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G06Q 10/10
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G06Q 10/20
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G06Q 30/016
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G06Q 10/063114
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G06Q 10/06312
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G06F 40/30
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G06F 40/40
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Patent abstract

System derives training change factors for services provided for training product user, priority assigned to training service ticket initiated by training product user, times of service ticket interactions associated with training service ticket, and/or age of training service ticket, and also for times of states of training service ticket. System uses training service ticket and training change factors to train change-based machine-learning model to predict change-based training probability that training product user escalated service for training service ticket. System derives change factors for services provided for product user, priority assigned to service ticket initiated by product user, times of service ticket interactions associated with service ticket, and/or age of service ticket, and also for times of states of training service ticket. System applies change-based machine-learning model to service ticket and change factors to predict change-based probability that product user escalates service for service ticket. System outputs change-based probability.

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