Pieter De Koninck

• PhD
• Team Lead AI at Silverfin

Within the field of process mining, several different trace clustering approaches exist for partitioning traces or process instances into similar groups. Typically, this partitioning is based on certain patterns or similarity between the traces, or driven by the discovery of a process model for each cluster. The main drawback of these techniques, h...

Within the field of process mining, several different trace clustering approaches exist for partitioning traces or process instances into similar groups. Typically, this partitioning is based on certain patterns or similarity between the traces, or driven by the discovery of a process model for each cluster. The main drawback of these techniques, h...

Given the complexity of real-life event logs, several trace clustering techniques have been proposed to partition an event log into subsets with a lower degree of variation. In general, these techniques assume that the number of clusters is known in advance. However, this will rarely be the case in practice. Therefore, this paper presents approache...

Trace clustering techniques are a set of approaches for partitioning traces or process instances into similar groups. Typically, this partitioning is based on certain patterns or similarity between the traces, or done by discovering a process model for each cluster of traces. In general, however, it is likely that clustering solutions obtained by t...

This paper presents a technique that aims to increase human understanding of trace clustering solutions. The clustering techniques under scrutiny stem from the process mining domain, where the clustering of process instances is deemed a useful technique to analyse process data with a large variety of behaviour. Until now, the most often used method...

An extensive amount of work has addressed the evaluation of process discovery techniques and the process models they discover based on concepts like fitness, precision, generalization and simplicity. In this paper, we claim that stability could be considered as an important supplementary evaluation dimension for process discovery next to accuracy a...

In recent years, a multitude of techniques has been proposed for the task of clustering traces. In general, these techniques either focus on optimizing their solution based on a certain type of similarity between the traces, such as the number of insertions and deletions needed to transform one trace into another; by mapping the traces onto a vecto...

Given the complexity of real-life event logs, several trace clustering techniques have been proposed to partition an event log into subsets with a lower degree of variation. In general, these techniques assume that the number of clusters is known in advance. However, this will rarely be the case in practice. Therefore, this paper is the first to pr...