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TJS
2010
182views more  TJS 2010»
13 years 6 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
AI
2006
Springer
13 years 7 months ago
Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Ole J. Mengshoel, David C. Wilkins, Dan Roth
GECCO
2009
Springer
143views Optimization» more  GECCO 2009»
14 years 2 months ago
Exploiting hierarchical clustering for finding bounded diameter minimum spanning trees on euclidean instances
The bounded diameter minimum spanning tree problem is an NP-hard combinatorial optimization problem arising, for example, in network design when quality of service is of concern. ...
Martin Gruber, Günther R. Raidl
COLING
2008
13 years 9 months ago
Unsupervised Induction of Labeled Parse Trees by Clustering with Syntactic Features
We present an algorithm for unsupervised induction of labeled parse trees. The algorithm has three stages: bracketing, initial labeling, and label clustering. Bracketing is done f...
Roi Reichart, Ari Rappoport
ICPR
2002
IEEE
14 years 8 months ago
Building the Topological Tree by Recursive FCM Color Clustering
In this paper we define a Topological Tree (TT) as a knowledge representation method that aims to describe important visual and spatial features of image regions, namely the color...
Rita Cucchiara, Costantino Grana, Andrea Prati, St...