loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Wellington Franco 1 ; Caio Viktor 1 ; Artur Oliveira 1 ; Gilvan Maia 1 ; Angelo Brayner 1 ; V. M. P. Vidal 1 ; Fernando Carvalho 1 and V. M. Pequeno 2

Affiliations: 1 Departamento de Computação, Federal University of Ceará, Fortaleza, Ceará, Brazil ; 2 TechLab, Departamento de Ciências e Tecnologias, Universidade Autónoma de Lisboa Luís de Camões, Portugal

Keyword(s): Question Answering Systems, Ontology, Knowledge Bases, Literature Survey.

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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 216.73.216.157

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Franco, W., Viktor, C., Oliveira, A., Maia, G., Brayner, A., Vidal, V. M. P., Carvalho, F., Pequeno and V. M. (2020). Ontology-based Question Answering Systems over Knowledge Bases: A Survey. In Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-423-7; ISSN 2184-4992, SciTePress, pages 532-539. DOI: 10.5220/0009392205320539

@conference{iceis20,
author={Wellington Franco and Caio Viktor and Artur Oliveira and Gilvan Maia and Angelo Brayner and V. M. P. Vidal and Fernando Carvalho and V. M. Pequeno},
title={Ontology-based Question Answering Systems over Knowledge Bases: A Survey},
booktitle={Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2020},
pages={532-539},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009392205320539},
isbn={978-989-758-423-7},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Ontology-based Question Answering Systems over Knowledge Bases: A Survey
SN - 978-989-758-423-7
IS - 2184-4992
AU - Franco, W.
AU - Viktor, C.
AU - Oliveira, A.
AU - Maia, G.
AU - Brayner, A.
AU - Vidal, V.
AU - Carvalho, F.
AU - Pequeno, V.
PY - 2020
SP - 532
EP - 539
DO - 10.5220/0009392205320539
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic