527 citations · 967 across the 30 of their papers we have counts for
6 papers · 1 filter
Discovering More Precise Process Models from Event Logs by Filtering Out Chaotic Activities
Niek Tax, Natalia Sidorova, Wil M. P. van der Aalst
Process Discovery is concerned with the automatic generation of a process model that describes a business process from execution data of that business process. Real life event logs…
The Imprecisions of Precision Measures in Process Mining
Niek Tax, Xixi Lu, Natalia Sidorova +2
In process mining, precision measures are used to quantify how much a process model overapproximates the behavior seen in an event log. Although several measures have been proposed…
Unsupervised Event Abstraction using Pattern Abstraction and Local Process Models
Felix Mannhardt, Niek Tax
Process mining analyzes business processes based on events stored in event logs. However, some recorded events may correspond to activities on a very low level of abstraction. When…
Interest-Driven Discovery of Local Process Models
Niek Tax, Benjamin Dalmas, Natalia Sidorova +2
Local Process Models (LPM) describe structured fragments of process behavior occurring in the context of less structured business processes. Traditional LPM discovery aims to gener…
Log-based Evaluation of Label Splits for Process Models
Niek Tax, Natalia Sidorova, Reinder Haakma +1
Process mining techniques aim to extract insights in processes from event logs. One of the challenges in process mining is identifying interesting and meaningful event labels that…
Mining Local Process Models
Niek Tax, Natalia Sidorova, Reinder Haakma +1
In this paper we describe a method to discover frequent behavioral patterns in event logs. We express these patterns as \emph{local process models}. Local process model mining can…