DocumentCode :
1865121
Title :
Danger Theory: A new approach in big data analysis
Author :
Lin Lu ; Yiwen Liang ; He Yang ; Chao Yang
Author_Institution :
Computer School, Wuhan University, China 430072
fYear :
2012
fDate :
3-5 March 2012
Firstpage :
739
Lastpage :
742
Abstract :
Danger Theory is a novel computing model inspired by biological immune systems which is some different with the traditional Artificial Immune Systems, especially the self non-self model. The Danger Theory concerns the potential dangers (which presents like the danger signals) rather than non-self pathogens, so the new computing model introduced into information analysis can take a new approach for big data processing on key features and properties choosing. The authors introduce some works on Danger Theory about the definition of danger, and the capture of danger signals, which could be helpful to increase the abilities of self-learning and intelligence in different applications.
Keywords :
Artificial Immune Systems; Big Data; Danger Theory; Information Analysis;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Automatic Control and Artificial Intelligence (ACAI 2012), International Conference on
Conference_Location :
Xiamen
Electronic_ISBN :
978-1-84919-537-9
Type :
conf
DOI :
10.1049/cp.2012.1083
Filename :
6492690
Link To Document :
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