most citedEvent Log Sampling for Predictive Monitoring

11 citations · 14 across the 6 of their papers we have counts for

collaborators

7 papers

cs.AI20221 cited

Probabilistic and Non-Deterministic Event Data in Process Mining: Embedding Uncertainty in Process Analysis Techniques

Marco Pegoraro

Process mining is a subfield of process science that analyzes event data collected in databases called event logs. Recently, novel types of event data have become of interest due t…

cs.DB2022

Uncertain Case Identifiers in Process Mining: A User Study of the Event-Case Correlation Problem on Click Data

Marco Pegoraro, Merih Seran Uysal, Tom-Hendrik Hülsmann +1

Among the many sources of event data available today, a prominent one is user interaction data. User activity may be recorded during the use of an application or website, resulting…

cs.AI2022

Process Mining on Uncertain Event Data

Marco Pegoraro

With the widespread adoption of process mining in organizations, the field of process science is seeing an increase in the demand for ad-hoc analysis techniques of non-standard eve…

cs.DB2022

An XES Extension for Uncertain Event Data

Marco Pegoraro, Merih Seran Uysal, Wil M. P. van der Aalst

Event data, often stored in the form of event logs, serve as the starting point for process mining and other evidence-based process improvements. However, event data in logs are of…

cs.LG202211 cited

Event Log Sampling for Predictive Monitoring

Mohammadreza Fani Sani, Mozhgan Vazifehdoostirani, Gyunam Park +3

Predictive process monitoring is a subfield of process mining that aims to estimate case or event features for running process instances. Such predictions are of significant intere…

cs.SE20221 cited

A Web-Based Tool for Comparative Process Mining

Madhavi Bangalore Shankara Narayana, Elisabetta Benevento, Marco Pegoraro +5

Process mining techniques enable the analysis of a wide variety of processes using event data. Among the available process mining techniques, most consider a single process perspec…