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» Detecting Anomalies in Graphs
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119
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CORR
2010
Springer
238views Education» more  CORR 2010»
15 years 1 months ago
Face Identification by SIFT-based Complete Graph Topology
This paper presents a new face identification system based on Graph Matching Technique on SIFT features extracted from face images. Although SIFT features have been successfully us...
Dakshina Ranjan Kisku, Ajita Rattani, Enrico Gross...
132
Voted
JOT
2010
216views more  JOT 2010»
14 years 11 months ago
A UML and Colored Petri Nets Integrated Modeling and Analysis Approach using Graph Transformation
Nowadays, UML is considered to be the standardized language for object-oriented modeling and analysis. However, UML cannot be used for automatic analyses and simulation. In this pa...
Elhillali Kerkouche, Allaoua Chaoui, El Bay Bouren...
87
Voted
KDD
2004
ACM
211views Data Mining» more  KDD 2004»
16 years 1 months ago
Towards parameter-free data mining
Most data mining algorithms require the setting of many input parameters. Two main dangers of working with parameter-laden algorithms are the following. First, incorrect settings ...
Eamonn J. Keogh, Stefano Lonardi, Chotirat (Ann) R...
ICC
2007
IEEE
120views Communications» more  ICC 2007»
15 years 7 months ago
Fixed-Period Packet Sampling and its Application to Flow Rate Estimation
Abstract— We propose a packet sampling strategy called fixedperiod sampling, which selects at most one packet in every fixedlength period. Under the fixed-period sampling, the...
Sadayoshi Ito, Kousuke Uchiyama, Shigeo Shioda
107
Voted
VIZSEC
2005
Springer
15 years 6 months ago
IDS RainStorm: Visualizing IDS Alarms
The massive amount of alarm data generated from intrusion detection systems is cumbersome for network system administrators to analyze. Often, important details are overlooked and...
Kulsoom Abdullah, Christopher P. Lee, Gregory J. C...