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» Algorithms for Clustering Data
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121
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AUSDM
2007
Springer
101views Data Mining» more  AUSDM 2007»
15 years 6 months ago
Exploratory Multilevel Hot Spot Analysis: Australian Taxation Office Case Study
Population based real-life datasets often contain smaller clusters of unusual sub-populations. While these clusters, called `hot spots', are small and sparse, they are usuall...
Denny, Graham J. Williams, Peter Christen
128
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ICISC
2004
169views Cryptology» more  ICISC 2004»
15 years 4 months ago
ADWICE - Anomaly Detection with Real-Time Incremental Clustering
Abstract. Anomaly detection, detection of deviations from what is considered normal, is an important complement to misuse detection based on attack signatures. Anomaly detection in...
Kalle Burbeck, Simin Nadjm-Tehrani
130
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WEBDB
2007
Springer
159views Database» more  WEBDB 2007»
15 years 8 months ago
A clustering-based sampling approach for refreshing search engine's database
Due to resource constraints, search engines usually have difficulties keeping the local database completely synchronized with the Web. To detect as many changes as possible, the ...
Qingzhao Tan, Ziming Zhuang, Prasenjit Mitra, C. L...
142
Voted
SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
15 years 4 months ago
Clustering from Constraint Graphs
In constrained clustering it is common to model the pairwise constraints as edges on the graph of observations. Using results from graph theory, we analyze such constraint graphs ...
Ari Freund, Dan Pelleg, Yossi Richter
139
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CVPR
2005
IEEE
16 years 4 months ago
A Bayesian Approach to Unsupervised Feature Selection and Density Estimation Using Expectation Propagation
We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
Shaorong Chang, Nilanjan Dasgupta, Lawrence Carin