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Data Analysis with Artificial Immune Systems and Cluster Analysis and Kohonen Networks: Some Comparisons

Timmis, Jon and Neal, Mark and Hunt, John (1999) Data Analysis with Artificial Immune Systems and Cluster Analysis and Kohonen Networks: Some Comparisons. In: IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics. IEEE, pp. 922-927. ISBN 0-7803-5731-0. (doi:10.1109/ICSMC.1999.823351) (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:21721)

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. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1109/ICSMC.1999.823351

Abstract

Knowledge discovery in databases (KDD) is still a relatively new and expanding field. To aid the KDD process, data mining methods are used to extract previously unknown patterns and trends in vast amounts of data. There exist a number of data mining techniques, taking methods from the machine learning, statistical analysis and pattern recognition communities, to name a few. Each technique has something different to offer over other techniques and each is suitable for different purposes giving certain benefits in varying situations. This paper examines a novel data analysis technique that is inspired by the human immune system: the artificial immune system (AIS). Immune system principles act as inspiration, allowing the creation of a network of cells that in effect clusters similar patterns and trends together. It is inspired by but not a model of the human immune system. This clustering allows the human user to effectively identify areas of similarity from the training data set that would previously have been unobtainable.

Item Type: Book section
DOI/Identification number: 10.1109/ICSMC.1999.823351
Uncontrolled keywords: data analysis; artificial immune systems; data mining; humans; immune system; databases; machine learning; statistical analysis; pattern recognition; training data
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: 03 Sep 2009 08:41 UTC
Last Modified: 16 Feb 2021 12:32 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/21721 (The current URI for this page, for reference purposes)
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