95 citations · 96 across the 3 of their papers we have counts for
7 papers
Discovering Object-Centric Petri Nets
Wil M. P. van der Aalst, Alessandro Berti
Techniques to discover Petri nets from event data assume precisely one case identifier per event. These case identifiers are used to correlate events, and the resulting discovered…
An Open-Source Integration of Process Mining Features into the Camunda Workflow Engine: Data Extraction and Challenges
Alessandro Berti, Wil van der Aalst, David Zang +1
Process mining provides techniques to improve the performance and compliance of operational processes. Although sometimes the term "workflow mining" is used, the application in the…
A Novel Token-Based Replay Technique to Speed Up Conformance Checking and Process Enhancement
Alessandro Berti, Wil van der Aalst
Token-based replay used to be the standard way to conduct conformance checking. With the uptake of more advanced techniques (e.g., alignment based), token-based replay got abandone…
Extracting Multiple Viewpoint Models from Relational Databases
Alessandro Berti, Wil van der Aalst
Much time in process mining projects is spent on finding and understanding data sources and extracting the event data needed. As a result, only a fraction of time is spent actually…
Increasing Scalability of Process Mining using Event Dataframes: How Data Structure Matters
Alessandro Berti
Process Mining is a branch of Data Science that aims to extract process-related information from event data contained in information systems, that is steadily increasing in amount.…
Process Mining for Python (PM4Py): Bridging the Gap Between Process- and Data Science
Alessandro Berti, Sebastiaan J. van Zelst, Wil van der Aalst
Process mining, i.e., a sub-field of data science focusing on the analysis of event data generated during the execution of (business) processes, has seen a tremendous change over t…