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» Efficiently Mining Regional Outliers in Spatial Data
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DATAMINE
2006
164views more  DATAMINE 2006»
13 years 7 months ago
Fast Distributed Outlier Detection in Mixed-Attribute Data Sets
Efficiently detecting outliers or anomalies is an important problem in many areas of science, medicine and information technology. Applications range from data cleaning to clinica...
Matthew Eric Otey, Amol Ghoting, Srinivasan Partha...
ICDM
2005
IEEE
133views Data Mining» more  ICDM 2005»
14 years 1 months ago
Parameter-Free Spatial Data Mining Using MDL
Consider spatial data consisting of a set of binary features taking values over a collection of spatial extents (grid cells). We propose a method that simultaneously finds spatia...
Spiros Papadimitriou, Aristides Gionis, Panayiotis...
SDM
2008
SIAM
97views Data Mining» more  SDM 2008»
13 years 9 months ago
Efficient Distribution Mining and Classification
We define and solve the problem of "distribution classification", and, in general, "distribution mining". Given n distributions (i.e., clouds) of multi-dimensi...
Yasushi Sakurai, Rosalynn Chong, Lei Li, Christos ...
DMKD
2004
ACM
127views Data Mining» more  DMKD 2004»
14 years 1 months ago
Discovering spatial patterns accurately with effective noise removal
Cluster analysis is a common approach to pattern discovery in spatial databases. While many clustering techniques have been developed, it is still challenging to discover implicit...
Yu Qian, Kang Zhang
TKDE
2002
168views more  TKDE 2002»
13 years 7 months ago
CLARANS: A Method for Clustering Objects for Spatial Data Mining
Spatial data mining is the discovery of interesting relationships and characteristics that may exist implicitly in spatial databases. To this end, this paper has three main contrib...
Raymond T. Ng, Jiawei Han