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VLDB
1998
ACM
192views Database» more  VLDB 1998»
10 years 2 months ago
Algorithms for Mining Distance-Based Outliers in Large Datasets
This paper deals with finding outliers (exceptions) in large, multidimensional datasets. The identification of outliers can lead to the discovery of truly unexpected knowledge in ...
Edwin M. Knorr, Raymond T. Ng
AUSDM
2007
Springer
222views Data Mining» more  AUSDM 2007»
10 years 4 months ago
CURIO: A Fast Outlier and Outlier Cluster Detection Algorithm for Large Datasets
Aaron Ceglar, John F. Roddick, David M. W. Powers
ICDM
2005
IEEE
187views Data Mining» more  ICDM 2005»
10 years 4 months ago
Parallel Algorithms for Distance-Based and Density-Based Outliers
An outlier is an observation that deviates so much from other observations as to arouse suspicion that it was generated by a different mechanism. Outlier detection has many applic...
Elio Lozano, Edgar Acuña
PAKDD
2009
ACM
149views Data Mining» more  PAKDD 2009»
10 years 3 months ago
A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data
Detecting outliers which are grossly diļ¬€erent from or inconsistent with the remaining dataset is a major challenge in real-world KDD applications. Existing outlier detection met...
Ke Zhang, Marcus Hutter, Huidong Jin
KDD
2006
ACM
142views Data Mining» more  KDD 2006»
10 years 11 months ago
Mining distance-based outliers from large databases in any metric space
Let R be a set of objects. An object o R is an outlier, if there exist less than k objects in R whose distances to o are at most r. The values of k, r, and the distance metric ar...
Yufei Tao, Xiaokui Xiao, Shuigeng Zhou
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