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dc.contributor.authorCollis, Nick
dc.contributor.authorFrommholz, Ingo
dc.date.accessioned2022-05-23T10:50:27Z
dc.date.available2022-05-23T10:50:27Z
dc.date.issued2021-12-29
dc.identifier.citationCollis N, Frommholz I (2021) 'Crowdsourced linked data question answering with AQUACOLD', ACM/IEEE Joint Conference on Digital Libraries (JCDL) - Champaign, IL, IEEE.en_US
dc.identifier.issn2575-7865
dc.identifier.doi10.1109/JCDL52503.2021.00043
dc.identifier.urihttp://hdl.handle.net/10547/625398
dc.description.abstractThere 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.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.urlhttps://ieeexplore.ieee.org/document/9651734en_US
dc.subjectLinked Dataen_US
dc.titleCrowdsourced linked data question answering with AQUACOLDen_US
dc.typeConference papers, meetings and proceedingsen_US
dc.identifier.eissn2575-8152
dc.contributor.departmentUniversity of Bedfordshireen_US
dc.contributor.departmentUniversity of Wolverhamptonen_US
dc.identifier.journal2021 ACM/IEEE JOINT CONFERENCE ON DIGITAL LIBRARIES (JCDL 2021)en_US
dc.date.updated2022-05-23T10:48:59Z
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