Even today, some of the basic analyzes have been performed manually or almost
without using specialized technologies, such as the Veterinary Medicine researchers
of the Federal University of Pará - Campus Castanhal, who carry out their analyzes
through statistical calculations using spreadsheets, taking enough time to analyze
them until useful information is actually detected. Thus, the present work describes
application knowledge discovery in Database’s process under dataset of researchers
of Veterinary Medicine to solve a real problem related to the detection of patterns
through the physical and morphological characteristics of monkeys of the species
Saimiri Collinsi living in captivity. With emphasis on the data mining stage, the following
assumptions are determined: determine which physical characteristics (arm and chest
skinfolds, weight and testicular volume) have a greater influence on the reproductive
season of animals. After, a new analysis under the parameters of seminal quality is
made as the objective is to identify the best period for the collection of semen of the
monkeys. All this process was performed through the association rules through the
Apriori and the FP-Growth algorithms, for a better performance of the results obtained
through an algorithmic comparison. It is worth mentioning that there is a need to
generate synthetic data (DS) due to the small amount of data available to perform the
algorithm training. Thus, each result obtained in this research was analyzed and
evaluated together with the experts of the area, so that there were no doubts or
misinterpretations thus ensuring their integrity.
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