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

Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

Authors

  • Maribel Acosta
  • Elena Simperl
  • Fabian Flöck
  • Maria Esther Vidal

Research Organisations

External Research Organisations

  • Karlsruhe Institute of Technology (KIT)
  • University of Southampton
  • GESIS - Leibniz Institute for the Social Sciences
  • Universidad Simon Bolivar
  • German National Library of Science and Technology (TIB)
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Details

Original languageEnglish
Title of host publicationThe Web Conference 2018
Subtitle of host publicationCompanion of the World Wide Web Conference, WWW 2018
Pages501-505
Number of pages5
ISBN (electronic)9781450356404
Publication statusPublished - Apr 2018
Event27th International World Wide Web, WWW 2018 - Lyon, France
Duration: 23 Apr 2018 → 27 Apr 2018

Publication series

NameACM Digital Library

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.

Keywords

    completeness, crowdsourcing, query execution, RDF, SPARQL

ASJC Scopus subject areas

Cite this

HARE: An Engine for Enhancing Answer Completeness of SPARQL Queries via Crowdsourcing. / Acosta, Maribel; Simperl, Elena; Flöck, Fabian et al.
The Web Conference 2018: Companion of the World Wide Web Conference, WWW 2018. 2018. p. 501-505 (ACM Digital Library).

Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

Acosta, M, Simperl, E, Flöck, F & Vidal, ME 2018, HARE: An Engine for Enhancing Answer Completeness of SPARQL Queries via Crowdsourcing. in The Web Conference 2018: Companion of the World Wide Web Conference, WWW 2018. ACM Digital Library, pp. 501-505, 27th International World Wide Web, WWW 2018, Lyon, France, 23 Apr 2018. https://doi.org/10.2139/ssrn.3199306, https://doi.org/10.1145/3184558.3186241
Acosta, M., Simperl, E., Flöck, F., & Vidal, M. E. (2018). HARE: An Engine for Enhancing Answer Completeness of SPARQL Queries via Crowdsourcing. In The Web Conference 2018: Companion of the World Wide Web Conference, WWW 2018 (pp. 501-505). (ACM Digital Library). https://doi.org/10.2139/ssrn.3199306, https://doi.org/10.1145/3184558.3186241
Acosta M, Simperl E, Flöck F, Vidal ME. HARE: An Engine for Enhancing Answer Completeness of SPARQL Queries via Crowdsourcing. In The Web Conference 2018: Companion of the World Wide Web Conference, WWW 2018. 2018. p. 501-505. (ACM Digital Library). Epub 2018 Apr 23. doi: 10.2139/ssrn.3199306, 10.1145/3184558.3186241
Acosta, Maribel ; Simperl, Elena ; Flöck, Fabian et al. / HARE: An Engine for Enhancing Answer Completeness of SPARQL Queries via Crowdsourcing. The Web Conference 2018: Companion of the World Wide Web Conference, WWW 2018. 2018. pp. 501-505 (ACM Digital Library).
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