Towards a danger theory inspired artificial immune system for web mining

Secker, Andrew D. and Freitas, Alex A. and Timmis, Jon (2005) Towards a danger theory inspired artificial immune system for web mining. In: Scime, A., ed. Web Mining: applications and techniques. Idea Group, pp. 145-168. ISBN 1-59140-415-0. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:14372)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.

Abstract

The natural immune system exhibits many properties that are of interest to the area of web mining. Of particular

interest is the dynamic nature of the immune system when compared with the dynamic nature of mining

information from the web. As part of a larger project to construct a large-scale dynamic web-mining system, this

chapter reports initial work on constructing an E-mail classifier system. The Artificial Immune System for Email

Classification (AISEC) is described in detail and compared with a traditional approach of naive Bayesian

classification. Results reported compare favorably with the Bayesian approach and this chapter highlights how

the Danger Theory from immunology can be used to further improve the performance of such an artificial

immune system.

Item Type:	Book section
Uncontrolled keywords:	artificial immune systems, web mining, data mining, e-mail classification
Subjects:	Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions:	Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User:	Mark Wheadon
Date Deposited:	24 Nov 2008 18:03 UTC
Last Modified:	16 Nov 2021 09:52 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/14372 (The current URI for this page, for reference purposes)

University of Kent Author Information

Secker, Andrew D..

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Freitas, Alex A..

Creator's ORCID:	https://orcid.org/0000-0001-9825-4700
CReDIT Contributor Roles:

Timmis, Jon.

Creator's ORCID:
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