Intelligent preprocessing to improve spam filtering accuracy

Authors

  • María Novo-Lourés Universidade de Vigo, Spain

Keywords:

Burst Processing, Data Pre-processing, Java, Pipeline Framework, Spam filtering, Feature engineering, Machine learning, Text representation

Abstract

This document presents an overview of the doctoral dissertation with the same title. This dissertation presents a comprehensive set of methodologies designed to improve the representation of information in spam filtering processes across multiple Internet protocols. Upon evaluation on December 21, 2021, it was awarded the prestigious distinction of cum laude.

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Published

2025-12-10

How to Cite

Novo-Lourés, M. (2025). Intelligent preprocessing to improve spam filtering accuracy. Inteligencia Artificial, 28(76), 311–314. Retrieved from https://journal.iberamia.org/index.php/intartif/article/view/1784

Issue

Vol. 28 No. 76 (2025): Inteligencia Artificial (December 2025)

Section

Theses Summaries

License

Copyright (c) 2025 Iberamia & The Authors

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Open Access publishing.
Lic. under Creative Commons CC-BY-NC
Inteligencia Artificial (Ed. IBERAMIA)
ISSN: 1988-3064 (on line).
(C) IBERAMIA & The Authors