Outlier detection from large distributed databases
In this paper, we present an innovative system, coined as DISTROD (aka DISTR ibuted O
utlier D etector), for detecting outliers, namely abnormal instances or observations, from
multiple large distributed databases. DISTROD is able to effectively detect the so-called
global outliers from distributed databases that are consistent with those produced by the
centralized detection paradigm. DISTROD is equipped with a number of
optimization/boosting strategies which empower it to significantly enhance its speed …
utlier D etector), for detecting outliers, namely abnormal instances or observations, from
multiple large distributed databases. DISTROD is able to effectively detect the so-called
global outliers from distributed databases that are consistent with those produced by the
centralized detection paradigm. DISTROD is equipped with a number of
optimization/boosting strategies which empower it to significantly enhance its speed …
Abstract
In this paper, we present an innovative system, coined as DISTROD (a.k.a DISTRibuted Outlier Detector), for detecting outliers, namely abnormal instances or observations, from multiple large distributed databases. DISTROD is able to effectively detect the so-called global outliers from distributed databases that are consistent with those produced by the centralized detection paradigm. DISTROD is equipped with a number of optimization/boosting strategies which empower it to significantly enhance its speed performance and reduce its communication overhead. Experimental evaluation demonstrates the good performance of DISTROD in terms of speed and communication overhead.
Springer
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