Artificial intelligence system with hierarchical machine learning for interaction session optimization

Artificial intelligence system with hierarchical machine learning for interaction session optimization

An intermediate result set is obtained from a first machine learning model whose input data set comprises values of a first set of properties associated with a session of operations. The intermediate result and a second set of properties associated with the session are provided as input to a second...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Bernet, Janick M, Verma, Prashant, Balakrishnan, Anoop
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
HANDLING RECORD CARRIERS
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:An intermediate result set is obtained from a first machine learning model whose input data set comprises values of a first set of properties associated with a session of operations. The intermediate result and a second set of properties associated with the session are provided as input to a second machine learning model. A value of at least one property of the first set is determined before a value of at least one property of the second set is determined. A particular action recommendation, based at least in part on output generated by the second machine learning model, is implemented.