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Artificial Immune Systems: Using the Immune System as Inspiration for Data Mining
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Author(s): Jonathan Timmis (University of Kent at Canterbury, UK)and Thomas Knight (University of Kent at Canterbury, UK)
Copyright: 2002
Pages: 22
Source title:
Data Mining: A Heuristic Approach
Source Author(s)/Editor(s): Hussein A. Abbass (University of New South Wales, Australia), Ruhul Sarker (University of New South Wales, Australia)and Charles S. Newton (University of New South Wales, Australia)
DOI: 10.4018/978-1-930708-25-9.ch011
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Abstract
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 to 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.
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