Objective classification of empirical probability distributions and the issue of event detection

Abstract

The paper concentrates on the issue of classification of empirical probability distributions (histograms), which is useful both in management situations and in event detection or event mining. While existing approaches to event detection concentrate on the use of selected moments or other characteristics of empirical probability distributions, we postulate that full empirical distribution preserves more of needed information then selected moments of this distribution, thus multiple criteria classification of distributions can be most effective in event detection.