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» Analyzing TCP Traffic Patterns Using Self Organizing Maps
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ICIAP
2005
ACM
12 years 5 months ago
Analyzing TCP Traffic Patterns Using Self Organizing Maps
The continuous evolution of the attacks against computer networks has given renewed strength to research on anomaly based Intrusion Detection Systems, capable of automatically dete...
Stefano Zanero
CGF
2010
189views more  CGF 2010»
11 years 5 months ago
Space-in-Time and Time-in-Space Self-Organizing Maps for Exploring Spatiotemporal Patterns
Spatiotemporal data pose serious challenges to analysts in geographic and other domains. Owing to the complexity of the geospatial and temporal components, this kind of data canno...
Gennady L. Andrienko, Natalia V. Andrienko, Sebast...
ICNC
2005
Springer
11 years 10 months ago
A Game-Theoretic Approach to Competitive Learning in Self-Organizing Maps
Abstract. Self-Organizing Maps (SOM) is a powerful tool for clustering and discovering patterns in data. Competitive learning in the SOM training process focusses on ļ¬nding a neu...
Joseph P. Herbert, Jingtao Yao
URBAN
2008
86views more  URBAN 2008»
11 years 5 months ago
Social area analysis, data mining, and GIS
: There is a long tradition of describing cities through a focus on the characteristics of their residents. A brief review of the history of this approach to describing cities high...
Seth E. Spielman, Jean-Claude Thill
HICSS
2006
IEEE
124views Biometrics» more  HICSS 2006»
11 years 11 months ago
Uncovering the Patterns in Pathology Ordering by Australian General Practitioners: A Data Mining Perspective
Pathology ordering by General Practitioners (GPs) is a significant contributor to rising health care costs both in Australia and worldwide. A thorough understanding of the nature ...
Zoe Yan Zhuang, Leonid Churilov, Ken Sikaris
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