activity
20142024
most citedProcess Mining for Python (PM4Py): Bridging the Gap Between Process- and Data Science

95 citations · 188 across the 16 of their papers we have counts for

collaborators
Showing 2022 · cs.DBShow all

5 papers · 2 filters

cs.DB2022

Interactive Process Identification and Selection from SAP ERP

Julian Weber, Alessandro Berti, Gyunam Park +2

SAP ERP is one of the most popular information systems supporting various organizational processes, e.g., O2C and P2P. However, the amount of processes and data contained in SAP ER…

cs.DB2022★ 50 cited

OC-PM: Analyzing Object-Centric Event Logs and Process Models

Alessandro Berti, Wil van der Aalst

Object-centric process mining is a novel branch of process mining that aims to analyze event data from mainstream information systems (such as SAP) more naturally, without being fo…

cs.DB2022★ 1 cited

Filtering and Sampling Object-Centric Event Logs

Alessandro Berti

The scalability of process mining techniques is one of the main challenges to tackling the massive amount of event data produced every day in enterprise information systems. To thi…

cs.DB2022

PM4Py-GPU: a High-Performance General-Purpose Library for Process Mining

Alessandro Berti, Minh Phan Nghia, Wil M. P. van der Aalst

Open-source process mining provides many algorithms for the analysis of event data which could be used to analyze mainstream processes (e.g., O2C, P2P, CRM). However, compared to c…

cs.DB2022

A Scalable Database for the Storage of Object-Centric Event Logs

Alessandro Berti, Anahita Farhang Ghahfarokhi, Gyunam Park +1

Object-centric process mining provides a set of techniques for the analysis of event data where events are associated to several objects. To store Object-centric Event Logs (OCELs)…