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196
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TJS
2010
182views more  TJS 2010»
15 years 5 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
233
Voted
ICDM
2010
IEEE
232views Data Mining» more  ICDM 2010»
15 years 4 months ago
gSkeletonClu: Density-Based Network Clustering via Structure-Connected Tree Division or Agglomeration
Community detection is an important task for mining the structure and function of complex networks. Many pervious approaches are difficult to detect communities with arbitrary size...
Heli Sun, Jianbin Huang, Jiawei Han, Hongbo Deng, ...
ICCV
2003
IEEE
16 years 8 months ago
Dominant Sets and Hierarchical Clustering
Dominant sets are a new graph-theoretic concept that has proven to be relevant in partitional (flat) clustering as well as image segmentation problems. However, in many computer v...
Massimiliano Pavan, Marcello Pelillo
RECOMB
2002
Springer
16 years 7 months ago
Probabilistic hierarchical clustering for biological data
Biological data, such as gene expression profiles or protein sequences, is often organized in a hierarchy of classes, where the instances assigned to "nearby" classes in...
Eran Segal, Daphne Koller
168
Voted
AI
2000
Springer
15 years 11 months ago
Keep It Simple: A Case-Base Maintenance Policy Based on Clustering and Information Theory
Abstract. Today’s case based reasoning applications face several challenges. In a typical application, the case bases grow at a very fast rate and their contents become increasin...
Qiang Yang, Jing Wu