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TJS
2010
182views more  TJS 2010»
13 years 8 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari
IPPS
2006
IEEE
14 years 4 months ago
Dynamic multi phase scheduling for heterogeneous clusters
Distributed computing systems are a viable and less expensive alternative to parallel computers. However, concurrent programming methods in distributed systems have not been studi...
Florina M. Ciorba, Theodore Andronikos, Ioannis Ri...
SDM
2007
SIAM
177views Data Mining» more  SDM 2007»
13 years 12 months ago
Multi-way Clustering on Relation Graphs
A number of real-world domains such as social networks and e-commerce involve heterogeneous data that describes relations between multiple classes of entities. Understanding the n...
Arindam Banerjee, Sugato Basu, Srujana Merugu
HIPC
2009
Springer
13 years 8 months ago
Comparing the performance of clusters, Hadoop, and Active Disks on microarray correlation computations
Abstract--Microarray-based comparative genomic hybridization (aCGH) offers an increasingly fine-grained method for detecting copy number variations in DNA. These copy number variat...
Jeffrey A. Delmerico, Nathanial A. Byrnes, Andrew ...
ICC
2011
IEEE
257views Communications» more  ICC 2011»
12 years 10 months ago
Increasing the Lifetime of Roadside Sensor Networks Using Edge-Betweenness Clustering
Abstract—Wireless Sensor Networks are proven highly successful in many areas, including military and security monitoring. In this paper, we propose a method to use the edge–bet...
Joakim Flathagen, Ovidiu Valentin Drugan, Paal E. ...