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With the increase in information on the Internet, the strive to find more effective tools for distinguishing between interesting and non-interesting material is increasing. Drawing analogies from the biological immune system, this paper presents an immune-inspired algorithm called AISEC that is capable of continuously classifying electronic mail as interesting and non-interesting without the need for re-training. Comparisons are drawn with a nave Bayesian classifier and it is shown that the proposed system performs as well as the nave Bayesian system and has a great potential for augmentation
@inproceedings{1759,
author = {Secker, A. and Freitas, A and Timmis, J.},
title = {{AISEC: An Artificial Immune System for E-mail Classification}},
month = {December},
year = {2003},
pages = {131-139},
keywords = {},
note = {},
doi = {},
url = {http://www.cs.kent.ac.uk/pubs/2003/1759},
publication_type = {inproceedings},
submission_id = {10707_1071763205},
booktitle = {Proceedings of the Congress on Evolutionary Computation},
editor = {Sarker, R. and Reynolds, R. and Abbass, H. and Kay-Chen, T. and McKay, R. and Essam, D and Gedeon, T.},
address = {Canberra. Australia},
organization = {IEEE},
refereed = {yes},
}