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

Abstract:

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.

Año de publicación:

2018

Keywords:

• Rdf
• crowdsourcing
• SPARQL
• Query execution
• completeness

Fuente:

scopus