| Summary: | Along with the popularity and ease of access from the internet, there
were some problems and spam is one of the most difficult to be solved. Thus, the
study of such messages becomes essential for the evolution of control tools. The use
of Bayesian statistical methods contributes to the identification and control of
receiving spam, however, such filters generate vast amounts of highly complex
statistical data to be analyzed. In this way, the work proposed in this article aims to
study and the applicability of Bayesian statistical calculations in the recognition of
spam in email and display the data generated by this analysis in 3D visual
representations organized intuitively and interactively, facilitating the decisionmaking
process.
|
|---|
