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

Gespeichert in:

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
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

container_end_page
container_issue
container_start_page
container_title
container_volume
creator	Bernet, Janick M Verma, Prashant Balakrishnan, Anoop
description	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.
format	Patent
fullrecord	<record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US10977711B1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US10977711B1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US10977711B13</originalsourceid><addsrcrecordid>eNqNi0EKAjEMRbtxIeod4gEEi4viUkVxr66HUNKZQCcdmoDo6Z0RD-DqPT7vz106VOPEkTEDi1HO3JJEAn2pUQ9Ptg46poo1dhzHqsdRhCATVmFpIZX6vVaMxkVASXViGYx7fuM0Lt0sYVZa_bhw68v5frpuaCgN6YCRhKx53Px2H0Lw_uh3_zQfJSpBIw</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Artificial intelligence system with hierarchical machine learning for interaction session optimization</title><source>esp@cenet</source><creator>Bernet, Janick M ; Verma, Prashant ; Balakrishnan, Anoop</creator><creatorcontrib>Bernet, Janick M ; Verma, Prashant ; Balakrishnan, Anoop</creatorcontrib><description>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.</description><language>eng</language><subject>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</subject><creationdate>2021</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210413&DB=EPODOC&CC=US&NR=10977711B1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210413&DB=EPODOC&CC=US&NR=10977711B1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Bernet, Janick M</creatorcontrib><creatorcontrib>Verma, Prashant</creatorcontrib><creatorcontrib>Balakrishnan, Anoop</creatorcontrib><title>Artificial intelligence system with hierarchical machine learning for interaction session optimization</title><description>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.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</subject><subject>HANDLING RECORD CARRIERS</subject><subject>PHYSICS</subject><subject>PRESENTATION OF DATA</subject><subject>RECOGNITION OF DATA</subject><subject>RECORD CARRIERS</subject><subject>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2021</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNi0EKAjEMRbtxIeod4gEEi4viUkVxr66HUNKZQCcdmoDo6Z0RD-DqPT7vz106VOPEkTEDi1HO3JJEAn2pUQ9Ptg46poo1dhzHqsdRhCATVmFpIZX6vVaMxkVASXViGYx7fuM0Lt0sYVZa_bhw68v5frpuaCgN6YCRhKx53Px2H0Lw_uh3_zQfJSpBIw</recordid><startdate>20210413</startdate><enddate>20210413</enddate><creator>Bernet, Janick M</creator><creator>Verma, Prashant</creator><creator>Balakrishnan, Anoop</creator><scope>EVB</scope></search><sort><creationdate>20210413</creationdate><title>Artificial intelligence system with hierarchical machine learning for interaction session optimization</title><author>Bernet, Janick M ; Verma, Prashant ; Balakrishnan, Anoop</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US10977711B13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2021</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</topic><topic>HANDLING RECORD CARRIERS</topic><topic>PHYSICS</topic><topic>PRESENTATION OF DATA</topic><topic>RECOGNITION OF DATA</topic><topic>RECORD CARRIERS</topic><topic>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</topic><toplevel>online_resources</toplevel><creatorcontrib>Bernet, Janick M</creatorcontrib><creatorcontrib>Verma, Prashant</creatorcontrib><creatorcontrib>Balakrishnan, Anoop</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Bernet, Janick M</au><au>Verma, Prashant</au><au>Balakrishnan, Anoop</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Artificial intelligence system with hierarchical machine learning for interaction session optimization</title><date>2021-04-13</date><risdate>2021</risdate><abstract>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.</abstract><oa>free_for_read</oa></addata></record>
fulltext	fulltext_linktorsrc
identifier
ispartof
issn
language	eng
recordid	cdi_epo_espacenet_US10977711B1
source	esp@cenet
subjects	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
title	Artificial intelligence system with hierarchical machine learning for interaction session optimization
url	https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T09%3A35%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=Bernet,%20Janick%20M&rft.date=2021-04-13&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS10977711B1%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true