PROCESSING A NATURAL LANGUAGE QUERY USING SEMANTICS MACHINE LEARNING

PROCESSING A NATURAL LANGUAGE QUERY USING SEMANTICS MACHINE LEARNING

A database server in a system supporting a cloud platform may train a machine learning model on a set of reports generated by a tenant. Each report of the set of reports may include a title and a query for one or more data objects associated with the tenant. The database server may identify a data l...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Acevedo, Nelson Esteban, Surepeddi, Srilakshmi Anusha, Zheng, Zuye
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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 Acevedo, Nelson Esteban
Surepeddi, Srilakshmi Anusha
Zheng, Zuye
description A database server in a system supporting a cloud platform may train a machine learning model on a set of reports generated by a tenant. Each report of the set of reports may include a title and a query for one or more data objects associated with the tenant. The database server may identify a data lineage for a data set associated with the tenant, where the data set is stored across multiple data sources and includes at least the one or more data objects. The database server may receive a natural language query associated with the data set and generate a set of candidate queries from the natural language query based on the machine learning model and the data lineage. The database server may select one or more of the candidate queries for display on a user interface based on a ranking of the plurality of candidate queries.
format Patent
fullrecord <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US2021149886A1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US2021149886A1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US2021149886A13</originalsourceid><addsrcrecordid>eNrjZHAJCPJ3dg0O9vRzV3BU8HMMCQ1y9FHwcfRzD3V0d1UIDHUNilQIBUsHu_o6-oV4Ogcr-Do6e3j6uSr4uDoG-QGleBhY0xJzilN5oTQ3g7Kba4izh25qQX58anFBYnJqXmpJfGiwkYGRoaGJpYWFmaOhMXGqABGqLNI</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>PROCESSING A NATURAL LANGUAGE QUERY USING SEMANTICS MACHINE LEARNING</title><source>esp@cenet</source><creator>Acevedo, Nelson Esteban ; Surepeddi, Srilakshmi Anusha ; Zheng, Zuye</creator><creatorcontrib>Acevedo, Nelson Esteban ; Surepeddi, Srilakshmi Anusha ; Zheng, Zuye</creatorcontrib><description>A database server in a system supporting a cloud platform may train a machine learning model on a set of reports generated by a tenant. Each report of the set of reports may include a title and a query for one or more data objects associated with the tenant. The database server may identify a data lineage for a data set associated with the tenant, where the data set is stored across multiple data sources and includes at least the one or more data objects. The database server may receive a natural language query associated with the data set and generate a set of candidate queries from the natural language query based on the machine learning model and the data lineage. The database server may select one or more of the candidate queries for display on a user interface based on a ranking of the plurality of candidate queries.</description><language>eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS</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&amp;date=20210520&amp;DB=EPODOC&amp;CC=US&amp;NR=2021149886A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20210520&amp;DB=EPODOC&amp;CC=US&amp;NR=2021149886A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Acevedo, Nelson Esteban</creatorcontrib><creatorcontrib>Surepeddi, Srilakshmi Anusha</creatorcontrib><creatorcontrib>Zheng, Zuye</creatorcontrib><title>PROCESSING A NATURAL LANGUAGE QUERY USING SEMANTICS MACHINE LEARNING</title><description>A database server in a system supporting a cloud platform may train a machine learning model on a set of reports generated by a tenant. Each report of the set of reports may include a title and a query for one or more data objects associated with the tenant. The database server may identify a data lineage for a data set associated with the tenant, where the data set is stored across multiple data sources and includes at least the one or more data objects. The database server may receive a natural language query associated with the data set and generate a set of candidate queries from the natural language query based on the machine learning model and the data lineage. The database server may select one or more of the candidate queries for display on a user interface based on a ranking of the plurality of candidate queries.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2021</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZHAJCPJ3dg0O9vRzV3BU8HMMCQ1y9FHwcfRzD3V0d1UIDHUNilQIBUsHu_o6-oV4Ogcr-Do6e3j6uSr4uDoG-QGleBhY0xJzilN5oTQ3g7Kba4izh25qQX58anFBYnJqXmpJfGiwkYGRoaGJpYWFmaOhMXGqABGqLNI</recordid><startdate>20210520</startdate><enddate>20210520</enddate><creator>Acevedo, Nelson Esteban</creator><creator>Surepeddi, Srilakshmi Anusha</creator><creator>Zheng, Zuye</creator><scope>EVB</scope></search><sort><creationdate>20210520</creationdate><title>PROCESSING A NATURAL LANGUAGE QUERY USING SEMANTICS MACHINE LEARNING</title><author>Acevedo, Nelson Esteban ; Surepeddi, Srilakshmi Anusha ; Zheng, Zuye</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US2021149886A13</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>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>Acevedo, Nelson Esteban</creatorcontrib><creatorcontrib>Surepeddi, Srilakshmi Anusha</creatorcontrib><creatorcontrib>Zheng, Zuye</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Acevedo, Nelson Esteban</au><au>Surepeddi, Srilakshmi Anusha</au><au>Zheng, Zuye</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>PROCESSING A NATURAL LANGUAGE QUERY USING SEMANTICS MACHINE LEARNING</title><date>2021-05-20</date><risdate>2021</risdate><abstract>A database server in a system supporting a cloud platform may train a machine learning model on a set of reports generated by a tenant. Each report of the set of reports may include a title and a query for one or more data objects associated with the tenant. The database server may identify a data lineage for a data set associated with the tenant, where the data set is stored across multiple data sources and includes at least the one or more data objects. The database server may receive a natural language query associated with the data set and generate a set of candidate queries from the natural language query based on the machine learning model and the data lineage. The database server may select one or more of the candidate queries for display on a user interface based on a ranking of the plurality of candidate queries.</abstract><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier
ispartof
issn
language eng
recordid cdi_epo_espacenet_US2021149886A1
source esp@cenet
subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
title PROCESSING A NATURAL LANGUAGE QUERY USING SEMANTICS MACHINE LEARNING
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-04T09%3A20%3A13IST&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=Acevedo,%20Nelson%20Esteban&rft.date=2021-05-20&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS2021149886A1%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