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dc.contributor.authorSchildgen, Johannes
dc.contributor.authorHeinz, Florian
dc.contributor.authorOlijnyk, Andreas
dc.contributor.authorLindenau, Arvid
dc.contributor.editorKönig-Ries, Birgitta
dc.contributor.editorScherzinger, Stefanie
dc.contributor.editorLehner, Wolfgang
dc.contributor.editorVossen, Gottfried
dc.date.accessioned2023-02-23T14:00:07Z
dc.date.available2023-02-23T14:00:07Z
dc.date.issued2023
dc.identifier.isbn978-3-88579-725-8
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/40361
dc.description.abstractTypical Alexa skills and other add-ons for voice assistants need to be custom developed for their one specific use case. This paper presents an approach to map arbitrary data sources (databases, APIs, services) to the relational model by using SQL/MED and to transform voice-based queries into SQL. The key challenges for such a universal skill are to correctly map the natural-language question into a SQL query on the correct source table in the federated database and to convert the result set back to a compact and well-understandable answer.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofBTW 2023
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-331
dc.subjectVoice Assistants
dc.subjectSQL/MED
dc.subjectNatural-Language Processing
dc.subjectUser interfaces for big data
dc.titleUsing SQL/MED to Query Heterogeneous Data Sources with Alexa Voice Commandsen
dc.typeText/Conference Paper
dc.identifier.doi10.18420/BTW2023-53
gi.conference.locationDresden, Germany
gi.conference.date06.-10. März 2023
gi.citation.startPage821
gi.citation.endPage828
gi.citation.publisherPlaceBonn


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