Emerging object-centric process mining techniques exploit event knowledge graphs to analyze event logs from multiple perspectives. However, current approaches rely on general-purpose graph tools that require technical expertise and lack features tailored to process mining. To address these limitations, we introduce SOUP, a user-friendly tool for constructing, navigating, and analyzing event knowledge graphs without manual queries. SOUP automates the creation of event knowledge graphs from event logs, offers filtering and aggregation operations, and supports large-scale data handling. This solution empowers users to conduct object-centric process mining analysis efficiently, facilitating the discovery of executed processes and the identification of related entities.

SOUP: Simplifying Event Knowledge Graph Management for Process Mining

Corradini F.;Pettinari S.;Re B.;Rossi L.
2025-01-01

Abstract

Emerging object-centric process mining techniques exploit event knowledge graphs to analyze event logs from multiple perspectives. However, current approaches rely on general-purpose graph tools that require technical expertise and lack features tailored to process mining. To address these limitations, we introduce SOUP, a user-friendly tool for constructing, navigating, and analyzing event knowledge graphs without manual queries. SOUP automates the creation of event knowledge graphs from event logs, offers filtering and aggregation operations, and supports large-scale data handling. This solution empowers users to conduct object-centric process mining analysis efficiently, facilitating the discovery of executed processes and the identification of related entities.
2025
Event Knowledge Graph
Graph Database
Object-Centric Process Mining
Process Mining
273
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11581/501465
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