Fishing monitor system data: A naïve bayes approach

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.