Timmis, Jon and Knight, Thomas (2001) Artificial Immune Systems: Using the Immune System as Inspiration for Data Mining. In: Abbass, H.A. and Sarker, Ruhul A. and Newton, Charles S., eds. Data Mining: A Heuristic Approach. Group Idea Publishing, Harrisburg PA, pp. 209-230. ISBN 978-1930708259.
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The immune system is highly distributed, highly adaptive, self-organising in nature, maintains a memory of past encounters, and has the ability to continually learn about new encounters. From a computational viewpoint, the immune system has much to offer by way of inspiration. Recently there has been growing interest in the use of the natural immune system as inspiration for the creation of novel approaches to computational problems; this field of research is referred as Immunological Computation (IC) or Artificial Immune Systems (AIS). This chapter describes the physiology of the immune system and provides a general introduction to Artificial Immune Systems. Significant applications that are relevant to data mining, in particular in the areas of machine learning and data analysis are discussed in detail. Attention is paid both to the salient characteristics of the application and the details of the algorithms. This chapter concludes with an evaluation of the current and future contributions of Artificial Immune Systems in Data Mining.
|Item Type:||Book section|
|Uncontrolled keywords:||artificial immune system, machine learning, immune metaphor, data mining|
|Subjects:||Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,|
|Divisions:||Faculties > Science Technology and Medical Studies > School of Computing > Applied and Interdisciplinary Informatics Group|
|Depositing User:||Mark Wheadon|
|Date Deposited:||24 Nov 2008 17:58|
|Last Modified:||04 Mar 2013 14:42|
|Resource URI:||http://kar.kent.ac.uk/id/eprint/13545 (The current URI for this page, for reference purposes)|
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