AISEC: An artificial immune system for e-mail classification

Andrew Secker; Alex A. Freitas; Jon Timmis

doi:10.1109/CEC.2003.1299566

AISEC: An artificial immune system for e-mail classification

Andrew Secker, Alex A. Freitas, Jon Timmis

Department of Computer Science

University of Kent

Research output: Contribution to conference › Paper › peer-review

81 Citations (Scopus)

Abstract

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 naive Bayesian classifier and it is shown that the proposed system performs as well as the naive Bayesian system and has a great potential for augmentation.

Original language	English
Pages	131-138
Number of pages	8
DOIs	https://doi.org/10.1109/CEC.2003.1299566
Publication status	Published - 2003
Event	2003 Congress on Evolutionary Computation, CEC 2003 - Canberra, ACT, Australia Duration: 08 Dec 2003 → 12 Dec 2003

Conference

Conference	2003 Congress on Evolutionary Computation, CEC 2003
Country/Territory	Australia
City	Canberra, ACT
Period	08 Dec 2003 → 12 Dec 2003

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10.1109/CEC.2003.1299566

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abstract = "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 naive Bayesian classifier and it is shown that the proposed system performs as well as the naive Bayesian system and has a great potential for augmentation.",

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AB - 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 naive Bayesian classifier and it is shown that the proposed system performs as well as the naive Bayesian system and has a great potential for augmentation.

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AISEC: An artificial immune system for e-mail classification

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