Querying Brazilian Educational Open Data using a Hybrid NLP-based Approach

Marco Antoni, Andrea Charão, Maria Franciscatto

Abstract

The need for capturing information suitable to the user has favored the development of Question Answering (QA) systems, whose main goal is retrieving a precise answer to a question expressed in Natural Language. Thus, these systems have been adopted in many domains to make data accessible, including Open Data. Although there are many QA approaches that access Open Data sources, querying Brazilian Open Data is still a research gap, possibly motivated by the complexity that Portuguese language presents to Natural Language Processing (NLP) approaches. For this reason, this paper proposes a hybrid NLP-based approach for querying Open Data of Brazilian Educational Census. The proposed solution is based on a combination of linguistic and rule-based NLP approaches, that are applied in two main processing stages (Text Preprocessing and Question Mapping) to identify the meaning of an input question and optimize the querying process. Our approach was evaluated through a QA prototype developed as a Web interface and showed feasible results, since concise and accurate answers were presented to the user.

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Paper Citation


in Harvard Style

Antoni M., Charão A. and Franciscatto M. (2021). Querying Brazilian Educational Open Data using a Hybrid NLP-based Approach. In Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-509-8, pages 120-130. DOI: 10.5220/0010486201200130


in Bibtex Style

@conference{iceis21,
author={Marco Antoni and Andrea Charão and Maria Franciscatto},
title={Querying Brazilian Educational Open Data using a Hybrid NLP-based Approach},
booktitle={Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2021},
pages={120-130},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010486201200130},
isbn={978-989-758-509-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Querying Brazilian Educational Open Data using a Hybrid NLP-based Approach
SN - 978-989-758-509-8
AU - Antoni M.
AU - Charão A.
AU - Franciscatto M.
PY - 2021
SP - 120
EP - 130
DO - 10.5220/0010486201200130