Below the lists of papers accepted in the ICPM 2022 Main and Demo tracks.
Main Track
- [77] Giacomo Acitelli, Marco Angelini, Silvia Bonomi, Fabrizio Maria Maggi, Andrea Marrella and Alessandro Palma. Context-Aware Trace Alignment with Automated Planning
- [4] Jan Niklas Adams, Daniel Schuster, Seth Schmitz, Günther Schuh and Wil van der Aalst. Defining Cases and Variants for Object-Centric Event Data
- [62] Bianka Bakullari and Wil M. P. van der Aalst. High-Level Event Mining: A Framework
- [40] Dina Bayomie, Kate Revoredo, Claudio Di Ciccio and Jan Mendling. Improving accuracy and explainability in event-case correlation via rule mining
- [30] Adam Burke, Sander Leemans, Moe Wynn, Wil van der Aalst and Arthur ter Hofstede. Stochastic Process Model-Log Quality Dimensions: An Experimental Study
- [31] Alessio Cecconi, Claudio Di Ciccio and Arik Senderovich. Measurement of Rule-based LTLf Declarative Process Specifications
- [51] Andrea Chiorrini, Claudia Diamantini, Laura Genga, Martina Pioli and Domenico Potena. Towards next-location prediction for process executions
- [74] David Chapela-Campa and Marlon Dumas. Modeling Extraneous Activity Delays in Business Process Simulation
- [28] Thomas Chatain and Neha Rino. Timed Alignments
- [63] Gamal Elkoumy and Marlon Dumas. Libra: High-Utility Anonymization of Event Logs for Process Mining via Subsampling
- [19] Jelmer Jan Koorn, Xixi Lu, Henrik Leopold, Niels Martin, Sam Verboven and Hajo A. Reijers. Mining Statistical Relations for Better Decision Making in Healthcare Processes
- [22] Tian Li and Sebastiaan van Zelst. Cache Enhanced Split-Point-Based Alignment Calculation
- [47] Alessandro Padella, Massimiliano de Leoni, Onur Doğan and Riccardo Galanti. Explainable Process Prescriptive Analytics
- [21] Alexander Stevens, Johannes De Smedt, Jari Peeperkorn and Jochen De Weerdt. Assessing the Robustness in Predictive Process Monitoring through Adversarial Attacks
- [53] Mozhgan Vazifehdoostirani, Laura Genga and Remco Dijkman. Encoding High-Level Control-Flow Construct Information for Process Outcome Prediction
- [56] Eric Verbeek. Discovering an S-Coverable WF-net using DiSCover
- [61] Akio Watanabe, Yousuke Takahashi, Hiroki Ikeuchi and Kotaro Matsuda. Grammar-Based Process Model Representation for Probabilistic Conformance Checking
Demo Track:
- [146] Alessandro Berti (PADS RWTH), Julian Weber (RWTH), Gyunam Park (PADS RWTH), Majid Rafiei (PADS RWTH) and Wil M.P. van der Aalst (PADS RWTH). Interactive Process Identification and Selection from SAP ERP.
- [150] Sander J.J. Leemans (RWTH Aachen). FilterTree: a Repeatable Branching XES Editor.
- [184] Humam Kourani (Fraunhofer FIT), Sebastiaan van Zelst (Fraunhofer FIT), Barry-Detlef Lehmann (Fraunhofer FIT), Gabriel Einsdorf (KNIME AG), Stefan Helfrich (KNIME AG) and Fabian Liße (KNIME AG). PM4KNIME: Process Mining Meets the KNIME Analytics Platform.
- [185] Andrea Burattin (Technical U. of Denmark). Streaming Process Mining with Beamline.
- [199] Nour Assy (Bonitasoft), Céline Souchet (Bonitasoft), Thomas Bouffard (Bonitasoft) and Olan Anesini (Bonitasoft). Visualization Libraries for Process Analytics.
- [200] Henrik Kirchmann (Humboldt-U. zu Berlin), Stephan Fahrenkrog-Petersen (Humbodt-U. zu Berlin), Martin Kabierski (Humboldt-U. zu Berlin), Han van der Aa (U. of Mannheim) and Matthias Weidlich (Humboldt-U. zu Berlin). Privacy-Preserving Process Mining with PM4Py.
- [203] Gamal Elkoumy (U. of Tartu), Alisa Pankova (Cybernetica AS) and Marlon Dumas (U. of Tartu). Amun: A tool for Differentially Private Release of Event Logs for Process Mining.
- [204] Andrea Burattin (Technical U. of Denmark), Barbara Re (U. of Camerino), Lorenzo Rossi (U. of Camerino) and Francesco Tiezzi (U. of Firenze). PURPLE: a PURPose-guided Log gEnerator.
- [207] Gerhardus A. W. M. van Hulzen (Hasselt U.), Gert Janssenswillen (Hasselt U.), Niels Martin (Hasselt U.) and Benoît Depaire (Hasselt U.). Process Analysis with bupaR 0.5.0: What’s New?
- [208] Mitchel Brunings (Eindhoven U. of Technology), Dirk Fahland (Eindhoven U. of Technology) and Eric Verbeek (Eindhoven U. of Technology). Discover Context-Rich LPMs (Extended Abstract).
- [209] Lotte Vugs (Waves Process Intelligence B.V.), Maarten Van Asseldonk (Waves Process Intelligence B.V.) and Niek van Son (Waves Process Intelligence B.V.). Konekti: A Data Preparation Platform for Process Mining (Extended Abstract).
- [211] Zahra Dasht Bozorgi (U. of Melbourne), Aleksei Kopõlov (U. of Tartu), Marlon Dumas (U. of Tartu), Marcello La Rosa (U. of Melbourne) and Artem Polyvyanyy (U. of Melbourne). ProLift: Automated Discovery of Causal Treatment Rules From Event Logs.
- [213] Martin Kabierski (Humboldt-U. zu Berlin), Stephan Fahrenkrog-Petersen (Humboldt-U. zu Berlin), Glenn Dittmann (Humboldt-U. zu Berlin) and Matthias Weidlich (Humboldt-U. zu Berlin). PaPPI: Privacy-aware Process Performance Indicators.
- [215] Daniel Barón-Espitia (U. de los Andes), Marlon Dumas (U. of Tartu) and Oscar González-Rojas (U. de los Andes). Coral: Conversational What-If Process Analysis.
- [223] István Koren (RWTH Aachen U., Chair of Process and Data Science). Music Score Analysis with Process Mining.
