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Authors: Jhonny Pincay ; Edy Portmann and Luis Terán

Affiliation: Human-IST Institute, University of Fribourg, Boulevard de Pérolles 90, Fribourg, Switzerland

Keyword(s): Linguistic Summaries, Traffic Data, Fuzzy Logic, Smart Cities, Smart Logistics.

Abstract: This case study article presents details about the implementation of an artifact that uses traffic data databases to mine linguistic summaries. The linguistic summaries are obtained and validated to ease the understanding of the data and to help users to convey information quickly and effectively. Through a web application that makes use of maps and accompanies them with the summaries, it was found that users with no experience in traffic analysis, do perceive that the mined linguistic summarizations helped them to understand data that would be rather complex even through figures and statistical measures. Nevertheless, although the linguistic summaries were perceived as useful, some users also found that they could provide some more details and have a finer granularity.

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Paper citation in several formats:
Pincay, J.; Portmann, E. and Terán, L. (2021). Mining Linguistic Summaries in Traffic. In Proceedings of the 13th International Joint Conference on Computational Intelligence (IJCCI 2021) - FCTA; ISBN 978-989-758-534-0; ISSN 2184-3236, SciTePress, pages 169-176. DOI: 10.5220/0010650100003063

@conference{fcta21,
author={Jhonny Pincay. and Edy Portmann. and Luis Terán.},
title={Mining Linguistic Summaries in Traffic},
booktitle={Proceedings of the 13th International Joint Conference on Computational Intelligence (IJCCI 2021) - FCTA},
year={2021},
pages={169-176},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010650100003063},
isbn={978-989-758-534-0},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computational Intelligence (IJCCI 2021) - FCTA
TI - Mining Linguistic Summaries in Traffic
SN - 978-989-758-534-0
IS - 2184-3236
AU - Pincay, J.
AU - Portmann, E.
AU - Terán, L.
PY - 2021
SP - 169
EP - 176
DO - 10.5220/0010650100003063
PB - SciTePress