Evolutionary Symbiotic Feature Selection for Email Spam Detection

Paulo Cortez, Rui Vaz, Miguel Rocha, Miguel Rio, Pedro Sousa


This work presents a symbiotic filtering approach enabling the exchange of relevant word features among different users in order to improve local anti-spam filters. The local spam filtering is based on a Content-Based Filtering strategy, where word frequencies are fed into a Naive Bayes learner. Several Evolutionary Algorithms are explored for feature selection, including the proposed symbiotic exchange of the most relevant features among different users. The experiments were conducted using a novel corpus based on the well known Enron datasets mixed with recent spam. The obtained results show that the symbiotic approach is competitive.


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Paper Citation

in Harvard Style

Cortez P., Vaz R., Rocha M., Rio M. and Sousa P. (2012). Evolutionary Symbiotic Feature Selection for Email Spam Detection . In Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-8565-21-1, pages 159-164. DOI: 10.5220/0004010201590164

in Bibtex Style

author={Paulo Cortez and Rui Vaz and Miguel Rocha and Miguel Rio and Pedro Sousa},
title={Evolutionary Symbiotic Feature Selection for Email Spam Detection},
booktitle={Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},

in EndNote Style

JO - Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Evolutionary Symbiotic Feature Selection for Email Spam Detection
SN - 978-989-8565-21-1
AU - Cortez P.
AU - Vaz R.
AU - Rocha M.
AU - Rio M.
AU - Sousa P.
PY - 2012
SP - 159
EP - 164
DO - 10.5220/0004010201590164