Please use this identifier to cite or link to this item:
Title: Ontology-based question answering systems over knowledge bases: a survey
Authors: Franco, Wellington
Avila, Caio Viktor Artur Oliveira S.
Maia, Gilvan
Brayner, Ângelo
Vidal, Vânia Maria P.
Carvalho, Fernando
Pequeno, Valéria
Keywords: Question Answering Systems
Knowledge bases
Literature survey
Issue Date: 2020
Publisher: SCITEPRESS Digital Library
Citation: Wellington 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: 532-539
Abstract: Searching 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.
Peer Reviewed: yes
metadata.dc.identifier.doi: 10.5220/0009392205320539
Appears in Collections:AUTONOMA TECHLAB - Artigos/Papers

Files in This Item:
File Description SizeFormat 
93922.pdf337,73 kBAdobe PDFThumbnail

FacebookTwitterDeliciousLinkedInDiggGoogle BookmarksMySpaceOrkut
Formato BibTex mendeley Endnote Logotipo do DeGóis Logotipo do Orcid 

This item is licensed under a Creative Commons License Creative Commons