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HARE: An Engine for Enhancing Answer Completeness of SPARQL Queries via Crowdsourcing




Published: 2018 April

Buchtitel: WWW ’18 Companion: The 2018 Web Conference Companion
Verlag: ACM
Erscheinungsort: New York, NY, USA
Organisation: The 2018 Web Conference
Nicht-referierte Veröffentlichung
BibTeX

Kurzfassung
We propose HARE, a SPARQL query engine that encompasses human-machine query processing to augment the completeness of query answers. We empirically assessed the effectiveness of HARE on 50 SPARQL queries over DBpedia. Experimental results clearly show that our solution accurately enhances answer completeness.

Weitere Informationen unter: Link


DOI Link: 10.1145/3184558.3186241



Forschungsgruppe

Web Science


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