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In the telecommunications services, fraud situations have a significant business impact. Due to the massive amounts of data handled, fraud detection stands as a very difficult and challenging task. In this paper , we propose the application of dynamic clustering over signatures to support this task. Traditional static clustering is applied to determine(More)
In this paper we tackle the problem of superimposed fraud detection in telecommunication systems. We propose two anomaly detection methods based on the concept of signatures. The first method relies on a signature deviation-based approach while the second on a dynamic clustering analysis. Experiments carried out with real data, voice call records from an(More)
Over the last decade, several algorithms for process discovery and process conformance have been proposed. Still, it is well-accepted that there is no dominant algorithm in any of these two disciplines, and then it is often difficult to apply them successfully. Most of these algorithms need a close-to expert knowledge in order to be applied satisfactorily.(More)
In this paper, we develop a simple and powerful multiscale model for the synthesis of nonGaussian, long-range dependent (LRD) network traac. Although wavelets eeectively decorrelate LRD data, wavelet-based models have generally been restricted by a Gaus-sianity assumption that can be unrealistic for traac. Using a mul-tiplicative superstructure on top of(More)
We develop a simple multiscale model for the analysis and synthesis of nonGaus-sian, long-range-dependent (LRD) network traac loads. The wavelet transform eeec-tively decorrelates LRD signals and hence is well-suited to model such data. However, traditional wavelet-based models are Gaussian in nature and so can at best match second-order statistics of(More)
Given an event log L, a control-flow discovery algorithm f , and a quality metric m, this paper faces the following problem: what are the parameters in f that mostly influence its application in terms of m when applied to L? This paper proposes a method to solve this problem , based on sensitivity analysis, a theory which has been successfully applied in(More)