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» Algorithms for Clustering Data
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ACSC
2005
IEEE
14 years 1 months ago
Unsupervised Anomaly Detection in Network Intrusion Detection Using Clusters
Most current network intrusion detection systems employ signature-based methods or data mining-based methods which rely on labelled training data. This training data is typically ...
Kingsly Leung, Christopher Leckie
PKDD
2007
Springer
109views Data Mining» more  PKDD 2007»
14 years 2 months ago
Matching Partitions over Time to Reliably Capture Local Clusters in Noisy Domains
Abstract. When seeking for small clusters it is very intricate to distinguish between incidental agglomeration of noisy points and true local patterns. We present the PAMALOC algor...
Frank Höppner, Mirko Böttcher
ISPA
2005
Springer
14 years 1 months ago
COMPACT: A Comparative Package for Clustering Assessment
Abstract. There exist numerous algorithms that cluster data-points from largescale genomic experiments such as sequencing, gene-expression and proteomics. Such algorithms may emplo...
Roy Varshavsky, Michal Linial, David Horn
EUROPAR
2001
Springer
14 years 24 days ago
Self-Organizing Hierarchical Cluster Timestamps
Distributed-system observation tools require an efficient data structure to store and query the partial-order of execution. Such data structures typically use vector timestamps to...
Paul A. S. Ward, David J. Taylor
ECML
2005
Springer
13 years 10 months ago
Clustering and Metaclustering with Nonnegative Matrix Decompositions
Although very widely used in unsupervised data mining, most clustering methods are affected by the instability of the resulting clusters w.r.t. the initialization of the algorithm ...
Liviu Badea