Personalized conversational recommendations by assistant systems
In one embodiment, a method includes receiving a user request from a client system associated with a user, generating a response to the user request which references one or more entities, generating a personalized recommendation based on the user request and the response, wherein the personalized re...
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| creator | Shah, Pararth Paresh Qiu, Yulong Liu, Honglei Subba, Rajen Xu, Hu Zhou, Hao Moon, Seungwhan Chai, Daniel Liu, Bing Li, Xiaolei |
| description | In one embodiment, a method includes receiving a user request from a client system associated with a user, generating a response to the user request which references one or more entities, generating a personalized recommendation based on the user request and the response, wherein the personalized recommendation references one or more of the entities of the response, and sending instructions for presenting the response and the personalized recommendation to the client system. |
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Chai, Daniel ; Liu, Bing ; Li, Xiaolei</creatorcontrib><description>In one embodiment, a method includes receiving a user request from a client system associated with a user, generating a response to the user request which references one or more entities, generating a personalized recommendation based on the user request and the response, wherein the personalized recommendation references one or more of the entities of the response, and sending instructions for presenting the response and the personalized recommendation to the client system.</description><language>eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; ELECTRIC COMMUNICATION TECHNIQUE ; ELECTRIC DIGITAL DATA PROCESSING ; ELECTRICITY ; PHYSICS ; TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION</subject><creationdate>2023</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=20230704&DB=EPODOC&CC=US&NR=11694281B1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230704&DB=EPODOC&CC=US&NR=11694281B1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Shah, Pararth Paresh</creatorcontrib><creatorcontrib>Qiu, Yulong</creatorcontrib><creatorcontrib>Liu, Honglei</creatorcontrib><creatorcontrib>Subba, Rajen</creatorcontrib><creatorcontrib>Xu, Hu</creatorcontrib><creatorcontrib>Zhou, Hao</creatorcontrib><creatorcontrib>Moon, Seungwhan</creatorcontrib><creatorcontrib>Chai, Daniel</creatorcontrib><creatorcontrib>Liu, Bing</creatorcontrib><creatorcontrib>Li, Xiaolei</creatorcontrib><title>Personalized conversational recommendations by assistant systems</title><description>In one embodiment, a method includes receiving a user request from a client system associated with a user, generating a response to the user request which references one or more entities, generating a personalized recommendation based on the user request and the response, wherein the personalized recommendation references one or more of the entities of the response, and sending instructions for presenting the response and the personalized recommendation to the client system.</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC COMMUNICATION TECHNIQUE</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>ELECTRICITY</subject><subject>PHYSICS</subject><subject>TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZHAISC0qzs9LzMmsSk1RSM7PKwPyE0syQUIKRanJ-bm5qXkpYIFihaRKhcTi4sziksS8EoXiyuKS1NxiHgbWtMSc4lReKM3NoOjmGuLsoZtakB-fWlyQmJyal1oSHxpsaGhmaWJkYehkaEyMGgB8BTLm</recordid><startdate>20230704</startdate><enddate>20230704</enddate><creator>Shah, Pararth Paresh</creator><creator>Qiu, Yulong</creator><creator>Liu, Honglei</creator><creator>Subba, Rajen</creator><creator>Xu, Hu</creator><creator>Zhou, Hao</creator><creator>Moon, Seungwhan</creator><creator>Chai, Daniel</creator><creator>Liu, Bing</creator><creator>Li, Xiaolei</creator><scope>EVB</scope></search><sort><creationdate>20230704</creationdate><title>Personalized conversational recommendations by assistant systems</title><author>Shah, Pararth Paresh ; Qiu, Yulong ; Liu, Honglei ; Subba, Rajen ; Xu, Hu ; Zhou, Hao ; Moon, Seungwhan ; Chai, Daniel ; Liu, Bing ; Li, Xiaolei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US11694281B13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2023</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC COMMUNICATION TECHNIQUE</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>ELECTRICITY</topic><topic>PHYSICS</topic><topic>TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION</topic><toplevel>online_resources</toplevel><creatorcontrib>Shah, Pararth Paresh</creatorcontrib><creatorcontrib>Qiu, Yulong</creatorcontrib><creatorcontrib>Liu, Honglei</creatorcontrib><creatorcontrib>Subba, Rajen</creatorcontrib><creatorcontrib>Xu, Hu</creatorcontrib><creatorcontrib>Zhou, Hao</creatorcontrib><creatorcontrib>Moon, Seungwhan</creatorcontrib><creatorcontrib>Chai, Daniel</creatorcontrib><creatorcontrib>Liu, Bing</creatorcontrib><creatorcontrib>Li, Xiaolei</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Shah, Pararth Paresh</au><au>Qiu, Yulong</au><au>Liu, Honglei</au><au>Subba, Rajen</au><au>Xu, Hu</au><au>Zhou, Hao</au><au>Moon, Seungwhan</au><au>Chai, Daniel</au><au>Liu, Bing</au><au>Li, Xiaolei</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Personalized conversational recommendations by assistant systems</title><date>2023-07-04</date><risdate>2023</risdate><abstract>In one embodiment, a method includes receiving a user request from a client system associated with a user, generating a response to the user request which references one or more entities, generating a personalized recommendation based on the user request and the response, wherein the personalized recommendation references one or more of the entities of the response, and sending instructions for presenting the response and the personalized recommendation to the client system.</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTING COUNTING ELECTRIC COMMUNICATION TECHNIQUE ELECTRIC DIGITAL DATA PROCESSING ELECTRICITY PHYSICS TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION |
| title | Personalized conversational recommendations by assistant systems |
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