2nd International Workshop on Leveraging Machine Learning in Process Mining (ML4PM)

by Paolo Ceravolo, Sylvio Barbon Jr., Annalisa Appice

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.
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6th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI)

by Artem Polyvyanyy, Claudio Di Ciccio, Sebastian Sardina, Renuka Sindhgatta, Arthur ter Hofstede

The Sixth International Workshop on Process Querying, Manipulation, and Intelligence (PQMI 2021) aims to provide a high-quality forum for researchers and practitioners to exchange research findings and ideas on methods and practices in the intersection of Process Mining and the research areas of Process Querying and Manipulation and Artificial Intelligence. Examples of problems tackled by the workshop themes include process compliance, process repair, process enhancement, and the use of AI techniques to improve process mining algorithms and architectures.
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4th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H)

by Carlos Fernandez-Llatas, Niels Martin, Owen Johnson, Marcos Sepúlveda, Emmanuel Helm

The 4th International Workshop on Process-Oriented Data Science for Healthcare 2021 (PODS4H 2021) aims to provide a high-quality forum for interdisciplinary researchers and practitioners (both in medicine and data/process science) to exchange research findings and ideas on data-driven healthcare process analysis techniques and practices. PODS4H research includes a wide range of topics from process mining techniques adapted for health care pathways, to practical issues related to the implementation of PODS methodologies in healthcare organizations.
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2nd International Workshop on Streaming Analytics for Process Mining (SA4PM)

by Marwan Hassani, Andrea Burattin, Thomas Seidl, Sebastiaan van Zelst

SA4PM workshop aims at promoting the use and development of new techniques to support streaming-based process analysis. It brings together practitioners and researchers from different communities: Process Mining, Stream Data Mining (mining time series, evolving graphs and scalable large data mining), Business Process Management, Database Systems and Information Systems with interest in online analysis and optimization of process-aware information systems with time, storage or complexity restrictions. Results of ongoing research, practical experiences and ideas for future research directions are welcome.
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2nd International Workshop on Event Data and Behavioral Analytics (EdbA)

by Benoît Depaire, Dirk Fahland, Francesco Leotta, Arik Senderovich

EdbA’21 calls for original work on the development of new (or novel applications of existing) techniques, algorithms and data structures for recording, storing, managing, processing, analyzing, and visualizing event data with the purpose of analyzing behavior of all kinds. Event data recorded at various sources, in various forms and at different granularity levels are considered, ranging from frequent sensor-based events in IoT settings to recordings of aggregate or long-running behavior involving time intervals and rich information.
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2nd International Workshop on Trust, Privacy and Security Aspects in Process Analytics (TPSA)

by Felix Mannhardt, Agnes Koschmider, Nathalie Baracaldo

Trust, privacy, and security have been largely neglected when considering the design and application of Process Mining. The TPSA workshop investigates this from two perspectives: (A) Responsible application of Process Mining including trust that the methods and their results are not misused. (B) Investigating privacy and security aspects of information systems by using Process Mining methods. Our objective is to give a forum for trust, privacy, and security aspects of Process Mining including concerns such as fairness, transparency, and accuracy.
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