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Crowdsourced linked data question answering with AQUACOLD

  • Nicholas Collis
    ,
  • Ingo Frommholz
  • University of Bedfordshire
    ,
  • University of Wolverhampton
Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Abstract

There is a need for Question Answering (QA) to return accurate answers to complex natural language questions over Linked Data, improving the accessibility of Linked Data (LD) search by abstracting the complexity of SPARQL whilst retaining its expressiveness. This work presents AQUACOLD, a LD QA system which harnesses the power of crowdsourcing to meet this need.

Publication Information

Output type

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 297-298 (2 pages)

Publication milestones

  • Published - 29/12/2021

Publication status

Published - 29/12/2021

Publisher

Institute of Electrical and Electronics Engineers Inc., United States

Publication series

  • Publication series name: Proceedings of the ACM/IEEE Joint Conference on Digital Libraries
    ISSN (Print): 1552-5996
    Volume: 2021-September

ISBN (Electronic)

9781665417709

External Publication IDs

  • handle.net: 10547/625398
  • Scopus: 85124250842

Host publication title

Proceedings - 2021 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2021

Host publication editors

  • J. Stephen Downie
  • Dana McKay
  • Hussein Suleman
  • David M. Nichols
  • Faryaneh Poursardar

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