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|Title=SPARQL Query Verbalization for Explaining Semantic Search Engine Queries
 
|Title=SPARQL Query Verbalization for Explaining Semantic Search Engine Queries
 
|Year=2014
 
|Year=2014
|Booktitle=ESWC 2013, LNCS 8465
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|Booktitle=Proceedings of the 11th Extended Semantic Web Conference (ESWC '14)
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|Pages=426-441
 
|Publisher=Springer
 
|Publisher=Springer
 
|Address=Heidelberg
 
|Address=Heidelberg
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|Series=LNCS
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|Number=8465
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}}
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{{Publikation Tool
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|Tool=Spartiqulation
 
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{{Publikation Details
 
{{Publikation Details
 
|Abstract=In this paper we introduce Spartiqulation, a system that translates SPARQL queries into English text. Our aim is to allow casual end users of semantic applications with limited to no expertise in the SPARQL query language to interact with these applications in a more intuitive way. The verbalization approach exploits domain-independent template-based natural language generation techniques, as well as linguistic cues in labels and URIs.
 
|Abstract=In this paper we introduce Spartiqulation, a system that translates SPARQL queries into English text. Our aim is to allow casual end users of semantic applications with limited to no expertise in the SPARQL query language to interact with these applications in a more intuitive way. The verbalization approach exploits domain-independent template-based natural language generation techniques, as well as linguistic cues in labels and URIs.
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|Download=ESWC2014 SPARQL.pdf,
 
|Projekt=XLike
 
|Projekt=XLike
 
|Forschungsgruppe=Wissensmanagement
 
|Forschungsgruppe=Wissensmanagement
 
}}
 
}}

Aktuelle Version vom 8. April 2015, 19:17 Uhr


SPARQL Query Verbalization for Explaining Semantic Search Engine Queries


SPARQL Query Verbalization for Explaining Semantic Search Engine Queries



Published: 2014

Buchtitel: Proceedings of the 11th Extended Semantic Web Conference (ESWC '14)
Nummer: 8465
Reihe: LNCS
Seiten: 426-441
Verlag: Springer
Erscheinungsort: Heidelberg

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Kurzfassung
In this paper we introduce Spartiqulation, a system that translates SPARQL queries into English text. Our aim is to allow casual end users of semantic applications with limited to no expertise in the SPARQL query language to interact with these applications in a more intuitive way. The verbalization approach exploits domain-independent template-based natural language generation techniques, as well as linguistic cues in labels and URIs.

Download: Media:ESWC2014 SPARQL.pdf

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