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Artificial Immune Systems

Authors :
Jon Timmis
Alex A. Freitas
Andrew Secker
Source :
Lecture Notes in Computer Science ISBN: 9783540407669
Publication Year :
2003
Publisher :
Springer Berlin Heidelberg, 2003.

Abstract

Within immunology, new theories are constantly being proposed that challenge current ways of thinking. These include new theories regarding how the immune system responds to pathogenic material. This conceptual paper takes one relatively new such theory: the Danger theory, and explores the relevance of this theory to the application domain of web mining. Central to the idea of Danger theory is that of a context dependant response to invading pathogens. This paper argues that this context dependency could be utilised as powerful metaphor for applications in web mining. An illustrative example adaptive mailbox filter is presented that exploits properties of the immune system, including the Danger theory. This is essentially a dynamical classification task: a task that this paper argues is well suited to the field of artificial immune systems, particularly when drawing inspiration from the Danger theory.

Details

ISBN :
978-3-540-40766-9
ISBNs :
9783540407669
Database :
OpenAIRE
Journal :
Lecture Notes in Computer Science ISBN: 9783540407669
Accession number :
edsair.doi...........5cc98d5206830b93c59ad8e323003081
Full Text :
https://doi.org/10.1007/b12020