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ACSC
2005
IEEE
15 years 5 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
COLING
2008
15 years 1 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
BIBE
2001
IEEE
188views Bioinformatics» more  BIBE 2001»
15 years 3 months ago
Interrelated Two-way Clustering: An Unsupervised Approach for Gene Expression Data Analysis
DNA arrays can be used to measure the expression levels of thousands of genes simultaneously. Currently most research focuses on the interpretation of the meaning of the data. How...
Chun Tang, Li Zhang, Aidong Zhang, Murali Ramanath...
EMNLP
2009
14 years 9 months ago
Unsupervised morphological segmentation and clustering with document boundaries
Many approaches to unsupervised morphology acquisition incorporate the frequency of character sequences with respect to each other to identify word stems and affixes. This typical...
Taesun Moon, Katrin Erk, Jason Baldridge
CVPR
1999
IEEE
16 years 1 months ago
Histogram Clustering for Unsupervised Image Segmentation
This paper introduces a novel statistical mixture model for probabilistic grouping of distributional histogram data. Adopting the Bayesian framework, we propose to perform anneale...
Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann