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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Ferreira, J. (2017). Data Mining Approach tool in Fishing Control Activity. In IMAM 2017. --
Exportar Referência (IEEE) 
J. C. Ferreira,  "Data Mining Approach tool in Fishing Control Activity", in IMAM 2017, --, 2017
Exportar BibTeX 
@inproceedings{ferreira2017_1732207827685,
	author = "Ferreira, J.",
	title = "Data Mining Approach tool in Fishing Control Activity",
	booktitle = "IMAM 2017",
	year = "2017",
	editor = "",
	volume = "",
	number = "",
	series = "",
	doi = "10.7307/ptt.v29i6.2871",
	publisher = "",
	address = "--",
	organization = "",
	url = "http://www.imamhomepage.org/imam2017/index.aspx"
}
Exportar RIS 
TY  - CPAPER
TI  - Data Mining Approach tool in Fishing Control Activity
T2  - IMAM 2017
AU  - Ferreira, J.
PY  - 2017
SN  - 1848-4069
DO  - 10.7307/ptt.v29i6.2871
CY  - --
UR  - http://www.imamhomepage.org/imam2017/index.aspx
AB  - In this research work is described about an implemented process to control the fish type and
weight in order to achieve the identification of non-compliant data reports. Such process is based in a mining model using Artificial Intelligence (AI) settings, namely based on data mining approaches of Naïve Bayes and Decision Trees. We identify fishing patterns based on past data, crossing Vessel Monitor System (VMS) data, with fishing reports (DPE), created by vessel master. Thus, it allows to identify possible non-conforming fishing report based on deviations from the patterns derived from the training mining model. We use real data
from Portuguese fishing activities.
ER  -