98 citations · 408 across the 10 of their papers we have counts for
12 papers
Exact and Approximated Log Alignments for Processes with Inter-case Dependencies
Dominique Sommers, Natalia Sidorova, Boudewijn F. van Dongen
The execution of different cases of a process is often restricted by inter-case dependencies through e.g., queueing or shared resources. Various high-level Petri net formalisms hav…
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…
Guided Interaction Exploration in Artifact-centric Process Models
Maikel L. van Eck, Natalia Sidorova, Wil M. P. van der Aalst
Artifact-centric process models aim to describe complex processes as a collection of interacting artifacts. Recent development in process mining allow for the discovery of such mod…
Mining Process Model Descriptions of Daily Life through Event Abstraction
Niek Tax, Natalia Sidorova, Reinder Haakma +1
Process mining techniques focus on extracting insight in processes from event logs. Process mining has the potential to provide valuable insights in (un)healthy habits and to contr…
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…
Generating Time-Based Label Refinements to Discover More Precise Process Models
Niek Tax, Emin Alasgarov, Natalia Sidorova +2
Process mining is a research field focused on the analysis of event data with the aim of extracting insights related to dynamic behavior. Applying process mining techniques on data…
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…
Heuristic Approaches for Generating Local Process Models through Log Projections
Niek Tax, Natalia Sidorova, Wil M. P. van der Aalst +1
Local Process Model (LPM) discovery is focused on the mining of a set of process models where each model describes the behavior represented in the event log only partially, i.e. su…
On Generation of Time-based Label Refinements
Niek Tax, Emin Alasgarov, Natalia Sidorova +1
Process mining is a research field focused on the analysis of event data with the aim of extracting insights in processes. Applying process mining techniques on data from smart hom…
Event Abstraction for Process Mining using Supervised Learning Techniques
Niek Tax, Natalia Sidorova, Reinder Haakma +1
Process mining techniques focus on extracting insight in processes from event logs. In many cases, events recorded in the event log are too fine-grained, causing process discovery…
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…