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Authors: Caio Viktor S. Avila 1 ; Anderson B. Calixto 1 ; Tulio Vidal Rolim 1 ; Wellington Franco 2 ; Amanda D. P. Venceslau 2 ; Vânia M. P. Vidal 1 ; Valéria M. Pequeno 3 and Francildo Felix De Moura 1

Affiliations: 1 Department of Computing, Federal University of Ceará, Campus do Pici, Fortaleza-CE and Brazil ; 2 Federal University of Ceará, Campus de Crateús, Crateús-CE and Brazil ; 3 TechLab, Departamento de Ciências e Tecnologias, Universidade Autónoma de Lisboa Luís de Camões and Portugal

Keyword(s): Chatbot, Data Integration, Semantic Web, Medical Informatics, Drugs.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence and Decision Support Systems ; Cloud Computing ; Coupling and Integrating Heterogeneous Data Sources ; Databases and Information Systems Integration ; Enterprise Information Systems ; Natural Language Interfaces to Intelligent Systems ; Semantic Web Technologies ; Services Science ; Software Agents and Internet Computing

Abstract: Brazil is one of the countries with the highest level of drug consumption in the world. By 2012 about 66% claimed to practice self-medication. Such activity can lead to a wide range of risks, including death from drug intoxication. Studies indicate that a lack of knowledge about drugs and their dangers is one of the main aggravating factors in this scenario. This work aims to universalize access to information about medications and their risks for different user profiles, especially Brazilian and lay users. In this paper, we presented the construction process of a Linked Data Mashup (LDM) integrating the datasets: consumer drug prices, government drug prices and drug’s risks in pregnant from ANVISA and SIDER from BIO2RDF. In addition, this work presents MediBot, an ontology-based chatbot capable of responding to requests in natural language in Portuguese through the instant messenger Telegram, smoothing the process to query the data. MediBot acts like a native language query interfac e on an LDM that works as an abstraction layer that provides an integrated view of multiple heterogeneous data sources. (More)

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Paper citation in several formats:
Avila, C.; Calixto, A.; Rolim, T.; Franco, W.; Venceslau, A.; Vidal, V.; Pequeno, V. and Felix De Moura, F. (2019). MediBot: An Ontology based Chatbot for Portuguese Speakers Drug’s Users. In Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-372-8; ISSN 2184-4984, SciTePress, pages 25-36. DOI: 10.5220/0007656400250036

@conference{iceis19,
author={Caio Viktor S. Avila. and Anderson B. Calixto. and Tulio Vidal Rolim. and Wellington Franco. and Amanda D. P. Venceslau. and Vânia M. P. Vidal. and Valéria M. Pequeno. and Francildo {Felix De Moura}.},
title={MediBot: An Ontology based Chatbot for Portuguese Speakers Drug’s Users},
booktitle={Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2019},
pages={25-36},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007656400250036},
isbn={978-989-758-372-8},
issn={2184-4984},
}

TY - CONF

JO - Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - MediBot: An Ontology based Chatbot for Portuguese Speakers Drug’s Users
SN - 978-989-758-372-8
IS - 2184-4984
AU - Avila, C.
AU - Calixto, A.
AU - Rolim, T.
AU - Franco, W.
AU - Venceslau, A.
AU - Vidal, V.
AU - Pequeno, V.
AU - Felix De Moura, F.
PY - 2019
SP - 25
EP - 36
DO - 10.5220/0007656400250036
PB - SciTePress