The interest in combining Machine Learning and Process Mining has seen increasing growth in the last few years along with the relevance of the ICPM conference. Thus, this workshop offers a focused environment to discuss new approaches, applications and their results to a wide audience, composed of researchers and practitioners. ML4PM will be held in Eindhoven, in conjunction with the ICPM conference.
This workshop invites papers that present works that lay in the intersection between machine learning and process mining. The event provides a suitable environment to discuss new approaches presented by researchers and practitioners. Main themes include automated process modeling, predictive process mining, application of deep learning techniques and online process mining. The workshop will count with leading researchers, engineers and scientists who are actively working on these topics.
Topics of interest for submission include, but are not limited to:
Contributions to all calls should be submitted electronically to the Workshop management system connecting to https://easychair.org/my/conference?conf=icpm2021. At least one author of each accepted paper is expected to participate in the conference and present his/her work.
Submissions must be original contributions that have not been published previously. Authors are requested to prepare submissions according to the format of the Lecture Notes in Business Information Processing (LNBIP) series by Springer href="http://www.springer.com/computer/lncs?SGWID=0-164-6-791344-0. Submissions must be in English and must not exceed 12 pages (including figures, bibliography and appendices). Each paper should contain a short abstract, clarifying the relation of the paper with the workshop topics, clearly state the problem being addressed, the goal of the work, the results achieved, and the relation to the literature.
Registrations are managed by the ICPM system
| Milestone | Deadline |
|---|---|
| Abstract Submission | August 19, 2021 |
| Paper Submission | August 26, 2021 |
| Notification of Acceptance | September 16, 2021 |
| Submission of Camera Ready Papers | September 30, 2021 |
| Workshop | November 1, 2021 |
| Post-workshop Camera-Ready Papers | November 16, 2021 |
| 09:00 - 10:15 | Research Papers: Predictive Process Monitoring |
Mohammadreza Fani Sani, Mozhgan Vazifedoostirani, Gyunam Park, Marco Pegoraro, Sebastiaan J. van Zelst and Wil van der Aalst. Event Log Sampling for Predictive Monitoring Mahsa Pourbafrani, Shreya Kar, Wil van der Aalst and Sebastian Kaiser. Remaining Time Prediction for Processes with Inter-Case Dynamics Andrea Chiorrini, Claudia Diamantini, Alex Mircoli and Domenico Potena. Exploiting Instance Graphs and Graph Neural Networks for next activity prediction |
| 10:15 - 11:00 | BREAK |
| 11:00 - 12:15 | Research Papers: Prescriptive and Responsible Process Mining |
Mahmoud Shoush and Marlon Dumas. Prescriptive Process Monitoring Under Resource Constraints: A Causal Inference Approach. Alexander Stevens, Johannes De Smedt and Jari Peeperkorn. Quantifying Explainability in Outcome-Oriented Predictive Process Monitoring Ruben Post, Iris Beerepoot, Xixi Lu, Stijn Kas, Sebastiaan Wiewel, Hajo A. Reijers and Angelique Koopman. Active Anomaly Detection for Key Item Selection in Process Auditing Jari Peeperkorn, Seppe Vanden Broucke and Jochen De Weerdt. Can deep neural networks learn process modelstructure? An assessment framework and analysis |
| 12:15 - 14:00 | LUNCH |
| 14:00-15:00 | Poster Session |
Vlad Paul Cosma, Gianmaria Tarantino, and Thomas Hildebrandt. Refining Events with Text Processing to Mine Processes in a Non-process-aware Municipal Document Management System - a Case Study Istvan Ketyko, Felix Mannhardt, Marwan Hassani, and Boudewijn Van Dongen. On the Skewness of Event Logs with Sequential Deep Learning Models for Suffix Generation Sylvio Barbon Junior, Paolo Ceravolo, Ernesto Damiani, and Gabriel Marques Tavares. Using Meta-learning to Recommend Process Discovery Methods Andrea Maldonado, Janina Sontheim and Thomas Seidl. Multilevel Anomaly Typification using the Performance Skyline |
|
| 15:00 - 15:45 | BREAK |
| 15:45 - 17:15 | Panel: Machine Learning and Process Mining - Marriage or Cohabitation? |
Wil van der Aalst, Ernesto Damiani, Chiara Di Francescomarino, Marlon Dumas |
Matthias Ehrendorfer, University of Vienna
Sarajane Marques Peres, University of São Paulo
Luís Paulo Faina Garcia, University of Brasilia
Michelangelo Ceci, University of Bari Aldo Moro
Gabriel Marques Tavares, Università degli Studi di Milano
Domenico Potena , Università Politechnica delle Marche
Antonella Guzzo, Università della Calabria
Natalia Sidorova, Eindhoven University of Technology
Irene Teinemaa, Booking.com
Wil van der Aalst, RWTH Aachen University
María Teresa Gómez, University of Seville
Mariangela Lazoi, University of Salento
Emerson Cabrera Paraiso, Pontifícia Universidade Católica do Paraná
Bruno Bogaz Zarpelão, State University of Londrina
Chiara Di Francescomarino, Fondazione Bruno Kessler
Fabrizio Maria Maggi, Free University of Bozen-Bolzano
Shridhar Devamane, APS College of Engineering, Bangalore
Niek Tax, Booking.com