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Ontologybased Question Answering Systems over Knowledge Bases: A Survey.

2020Journal article Open access
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dc.contributor.authorFranco, Wellington
dc.contributor.authorAvila, Caio Viktor Artur Oliveira S.
dc.contributor.authorMaia, Gilvan
dc.contributor.authorBrayner, Ângelo
dc.contributor.authorVidal, Vânia Maria P.
dc.contributor.authorCarvalho, Fernando
dc.contributor.authorPequeno, Valéria M.
dc.date.accessioned2025-05-16T14:44:06Z
dc.date.available2025-05-16T14:44:06Z
dc.date.issued2020
dc.description.abstractSearching relevant, specific information in big data volumes is quite a challenging task. Despite the numerous strategies in the literature to tackle this problem, this task is usually carried out by resorting to a Question Answering (QA) systems. There are many ways to build a QA system, such as heuristic approaches, machine learning, and ontologies. Recent research focused their efforts on ontology-based methods since the resulting QA systems can benefit from knowledge modeling. In this paper, we present a systematic literature survey on ontology-based QA systems regarding any questions. We also detail the evaluation process carried out in these systems and discuss how each approach differs from the others in terms of the challenges faced and strategies employed. Finally, we present the most prominent research issues still open in the field.eng
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationWellington Franco, Caio Viktor S. Avila, Artur Oliveira, Gilvan Maia, Angelo Brayner, Vânia Maria P. Vidal, Fernando Carvalho, Valéria Magalhães Pequeno: Ontology-based Question Answering Systems over Knowledge Bases: A Survey. ICEIS (1) 2020: 532-539pt_PT
dc.identifier.doi10.5220/0009392205320539
dc.identifier.isbn978-989-758-423-7
dc.identifier.urihttp://hdl.handle.net/10400.26/57841
dc.language.isoengpt_PT
dc.peerreviewedyes
dc.publisherSCITEPRESS Digital Librarypt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-sa/4.0/
dc.subjectQuestion Answering Systems
dc.subjectOntology
dc.subjectKnowledge bases
dc.subjectLiterature survey
dc.titleOntologybased Question Answering Systems over Knowledge Bases: A Survey.pt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage539pt_PT
oaire.citation.startPage532pt_PT
oaire.citation.titleProceedings of the 22nd International Conference on Enterprise Information Systems (ICEIS 2020)
oaire.citation.volume1
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT

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