DBPal: A learned NL-interface for databases

dc.citation.epage1768en_US
dc.citation.spage1765en_US
dc.contributor.authorBasık, Fuaten_US
dc.contributor.authorHättasch, B.en_US
dc.contributor.authorIlkhechi, A.en_US
dc.contributor.authorUsta, A.en_US
dc.contributor.authorRamaswamy, S.en_US
dc.contributor.authorUtama, P.en_US
dc.contributor.authorWeir, N.en_US
dc.contributor.authorBinnig, C.en_US
dc.contributor.authorCetintemel, U.en_US
dc.coverage.spatialHouston, TX, USAen_US
dc.date.accessioned2019-02-21T16:06:43Z
dc.date.available2019-02-21T16:06:43Z
dc.date.issued2018en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionDate of Conference: June 10 - 15, 2018en_US
dc.description.abstractIn this demo, we present DBPal, a novel data exploration tool with a natural language interface. DBPal leverages recent advances in deep models to make query understanding more robust in the following ways: First, DBPal uses novel machine translation models to translate natural language statements to SQL, making the translation process more robust to paraphrasing and linguistic variations. Second, to support the users in phrasing questions without knowing the database schema and the query features, DBPal provides a learned auto-completion model that suggests to users partial query extensions during query formulation and thus helps to write complex queries.
dc.description.provenanceMade available in DSpace on 2019-02-21T16:06:43Z (GMT). No. of bitstreams: 1 Bilkent-research-paper.pdf: 222869 bytes, checksum: 842af2b9bd649e7f548593affdbafbb3 (MD5) Previous issue date: 2018en
dc.identifier.doi10.1145/3183713.3193562
dc.identifier.isbn9781450317436
dc.identifier.issn0730-8078
dc.identifier.urihttp://hdl.handle.net/11693/50326
dc.language.isoEnglish
dc.publisherACM
dc.relation.isversionofhttps://doi.org/10.1145/3183713.3193562
dc.source.titleSIGMOD '18 Proceedings of the 2018 International Conference on Management of Dataen_US
dc.titleDBPal: A learned NL-interface for databasesen_US
dc.typeConference Paperen_US

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