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    Crowdsourced linked data question answering with AQUACOLD

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    Authors
    Collis, Nick
    Frommholz, Ingo
    Affiliation
    University of Bedfordshire
    University of Wolverhampton
    Issue Date
    2021-12-29
    Subjects
    Linked Data
    
    Metadata
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    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.
    Citation
    Collis N, Frommholz I (2021) 'Crowdsourced linked data question answering with AQUACOLD', ACM/IEEE Joint Conference on Digital Libraries (JCDL) - Champaign, IL, IEEE.
    Publisher
    IEEE
    Journal
    2021 ACM/IEEE JOINT CONFERENCE ON DIGITAL LIBRARIES (JCDL 2021)
    URI
    http://hdl.handle.net/10547/625398
    DOI
    10.1109/JCDL52503.2021.00043
    Additional Links
    https://ieeexplore.ieee.org/document/9651734
    Type
    Conference papers, meetings and proceedings
    Language
    en
    ISSN
    2575-7865
    EISSN
    2575-8152
    ae974a485f413a2113503eed53cd6c53
    10.1109/JCDL52503.2021.00043
    Scopus Count
    Collections
    Computing

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