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DPD
2002
125views more  DPD 2002»
13 years 7 months ago
Parallel Mining of Outliers in Large Database
Data mining is a new, important and fast growing database application. Outlier (exception) detection is one kind of data mining, which can be applied in a variety of areas like mon...
Edward Hung, David Wai-Lok Cheung
ECAI
2010
Springer
13 years 7 months ago
Mining Outliers with Adaptive Cutoff Update and Space Utilization (RACAS)
Recently the efficiency of an outlier detection algorithm ORCA was improved by RCS (Randomization with faster Cutoff update and Space utilization after pruning), which changes the ...
Chi-Cheong Szeto, Edward Hung
KDD
2010
ACM
250views Data Mining» more  KDD 2010»
13 years 9 months ago
On community outliers and their efficient detection in information networks
Linked or networked data are ubiquitous in many applications. Examples include web data or hypertext documents connected via hyperlinks, social networks or user profiles connected...
Jing Gao, Feng Liang, Wei Fan, Chi Wang, Yizhou Su...
ICDM
2010
IEEE
185views Data Mining» more  ICDM 2010»
13 years 5 months ago
Detecting Non-compliant Consumers in Spatio-Temporal Health Data: A Case Study from Medicare Australia
This paper describes our experience with applying data mining techniques to the problem of fraud detection in spatio-temporal health data in Medicare Australia. A modular framework...
Kee Siong Ng, Yin Shan, D. Wayne Murray, Alison Su...
ICTAI
2002
IEEE
14 years 15 days ago
Data Mining for Selective Visualization of Large Spatial Datasets
Data mining is the process of extracting implicit, valuable, and interesting information from large sets of data. Visualization is the process of visually exploring data for patte...
Shashi Shekhar, Chang-Tien Lu, Pusheng Zhang, Ruli...