Fishing monitor system data: A naïve bayes approach

Joao C. Ferreira, Serge Lage, Iola Pinto, Nuno Antunes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper discusses the results of an applied research on the fishing activity based on a monitor system developed by a company and fishing reports produced at the end of each fishing activity. Due to economic interests combined with fishing limitations there is a natural tendency for wrong reporting. We apply Data Mining (DM) methodologies to find fishing patterns. These DM techniques in SQL tool allow to deal with the high volume of this data set and determine the major factors that influence fishing activity.

Original languageEnglish
Title of host publicationIntelligent Systems Design and Applications - 16th International Conference on Intelligent Systems Design and Applications, ISDA 2016
EditorsPaulo Novais, Ana Maria Madureira, Ajith Abraham, Dorabela Gamboa
PublisherSpringer Verlag
Pages582-591
Number of pages10
ISBN (Print)9783319534794
DOIs
Publication statusPublished - 2017
Event16th International Conference on Intelligent Systems Design and Applications, ISDA 2016 - Porto, Portugal
Duration: 16 Dec 201618 Dec 2016

Publication series

NameAdvances in Intelligent Systems and Computing
Volume557
ISSN (Print)2194-5357

Conference

Conference16th International Conference on Intelligent Systems Design and Applications, ISDA 2016
CountryPortugal
CityPorto
Period16/12/1618/12/16

Keywords

  • Data mining
  • Fishing activity
  • Naïve bayes
  • Patterns

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  • Cite this

    Ferreira, J. C., Lage, S., Pinto, I., & Antunes, N. (2017). Fishing monitor system data: A naïve bayes approach. In P. Novais, A. M. Madureira, A. Abraham, & D. Gamboa (Eds.), Intelligent Systems Design and Applications - 16th International Conference on Intelligent Systems Design and Applications, ISDA 2016 (pp. 582-591). (Advances in Intelligent Systems and Computing; Vol. 557). Springer Verlag. https://doi.org/10.1007/978-3-319-53480-0_57