Negative selection as a means of discovering unknown temporal patterns

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The temporal nature of negative selection is an under exploited area. In a negative selection system, newly generated antibodies go through a maturing phase, and the survivors of the phase then wait to be activated by the incoming antigens after certain number of matches. These without having enough matches will age and die, while these with enough matches (i.e., being activated) will become active detectors. A currently active detector may also age and die if it cannot find any match in a pre-defined (lengthy) period of time. Therefore, what matters in a negative selection system is the dynamics of the involved parties in the current time window, not the whole time duration, which may be up to eternity. This property has the potential to define the uniqueness of negative selection in comparison with the other approaches. On the other hand, a negative selection system is only trained with “normal" data samples. It has to learn and discover unknown “abnormal" data patterns on the fly by itself. Consequently, it is more appreciate to utilize negation selection as a system for pattern discovery and recognition rather than just pattern recognition. In this paper, we study the potential of using negative selection in discovering unknown temporal patterns.
Original languageEnglish
Title of host publicationICIS 2010: International Conference on Intelligent Systems
EditorsMary Lacity, Sal March, Fred Niederman
Place of PublicationOnline
PublisherWorld Academy of Science, Engineering and Technology
Number of pages7
ISBN (Print)9780615418988
Publication statusPublished - 2010
EventICIS 2010: "International Conference on Intelligent Systems" - Tokyo, Japan
Duration: 26 May 201028 May 2010


ConferenceICIS 2010: "International Conference on Intelligent Systems"


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