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ORCIDBusiness Process Management 2016: Rio de Janeiro, Brazil
- Marcello La Rosa, Peter Loos, Oscar Pastor:
Business Process Management - 14th International Conference, BPM 2016, Rio de Janeiro, Brazil, September 18-22, 2016. Proceedings. Lecture Notes in Computer Science 9850, Springer 2016, ISBN 978-3-319-45347-7
Keynotes
- Richard Hull, Hamid R. Motahari Nezhad:
Rethinking BPM in a Cognitive World: Transforming How We Learn and Perform Business Processes. 3-19 - Giancarlo Guizzardi, Nicola Guarino
, João Paulo A. Almeida:
Ontological Considerations About the Representation of Events and Endurants in Business Models. 20-36
Automated Discovery
- Boudewijn F. van Dongen, Josep Carmona, Thomas Chatain:
A Unified Approach for Measuring Precision and Generalization Based on Anti-alignments. 39-56 - Pieter De Koninck, Jochen De Weerdt:
A Stability Assessment Framework for Process Discovery Techniques. 57-72 - Gert Janssenswillen, Toon Jouck, Mathijs Creemers, Benoît Depaire:
Measuring the Quality of Models with Respect to the Underlying System: An Empirical Study. 73-89 - Xixi Lu, Dirk Fahland, Frank J. H. M. van den Biggelaar, Wil M. P. van der Aalst:
Handling Duplicated Tasks in Process Discovery by Refining Event Labels. 90-107 - Javier de San Pedro, Jordi Cortadella:
Discovering Duplicate Tasks in Transition Systems for the Simplification of Process Models. 108-124 - Felix Mannhardt, Massimiliano de Leoni, Hajo A. Reijers, Wil M. P. van der Aalst, Pieter J. Toussaint:
From Low-Level Events to Activities - A Pattern-Based Approach. 125-141 - Maikel L. van Eck, Natalia Sidorova, Wil M. P. van der Aalst:
Discovering and Exploring State-Based Models for Multi-perspective Processes. 142-157 - Fabrizio Maria Maggi, Marco Montali, Claudio Di Ciccio, Jan Mendling:
Semantical Vacuity Detection in Declarative Process Mining. 158-175
Conformance Checking
- Andreas Rogge-Solti, Arik Senderovich, Matthias Weidlich, Jan Mendling, Avigdor Gal:
In Log and Model We Trust? A Generalized Conformance Checking Framework. 179-196 - Farbod Taymouri, Josep Carmona:
A Recursive Paradigm for Aligning Observed Behavior of Large Structured Process Models. 197-214
Modeling Foundations
- Diego Calvanese, Marlon Dumas, Ülari Laurson, Fabrizio Maria Maggi, Marco Montali, Irene Teinemaa:
Semantics and Analysis of DMN Decision Tables. 217-233 - Dirk Fahland, Hagen Völzer:
Dynamic Skipping and Blocking and Dead Path Elimination for Cyclic Workflows. 234-251 - Mirela Botezatu, Hagen Völzer, Lothar Thiele:
The Complexity of Deadline Analysis for Workflow Graphs with Multiple Resources. 252-268
Understandability of Process Representations
- Han van der Aa, Henrik Leopold, Hajo A. Reijers:
Dealing with Behavioral Ambiguity in Textual Process Descriptions. 271-288 - Oktay Türetken, Tessa Rompen, Irene T. P. Vanderfeesten, Ahmet Dikici, Jan van Moll:
The Effect of Modularity Representation and Presentation Medium on the Understandability of Business Process Models in BPMN. 289-307 - Julius Köpke, Jianwen Su:
Towards Quality-Aware Translations of Activity-Centric Processes to Guard Stage Milestone. 308-325
Runtime Management
- Ingo Weber, Xiwei Xu, Régis Riveret, Guido Governatori, Alexander Ponomarev, Jan Mendling:
Untrusted Business Process Monitoring and Execution Using Blockchain. 329-347 - Walid Fdhila, Manuel Gall, Stefanie Rinderle-Ma, Juergen Mangler, Conrad Indiono:
Classification and Formalization of Instance-Spanning Constraints in Process-Driven Applications. 348-364 - Oscar González Rojas, Sebastián Lesmes:
Value at Risk Within Business Processes: An Automated IT Risk Governance Approach. 365-380
Prediction
- Raffaele Conforti, Sven Fink, Jonas Manderscheid, Maximilian Röglinger:
PRISM - A Predictive Risk Monitoring Approach for Business Processes. 383-400 - Irene Teinemaa, Marlon Dumas, Fabrizio Maria Maggi, Chiara Di Francescomarino:
Predictive Business Process Monitoring with Structured and Unstructured Data. 401-417 - Arik Senderovich, Alexander Shleyfman, Matthias Weidlich, Avigdor Gal, Avishai Mandelbaum:
P ^3 -Folder: Optimal Model Simplification for Improving Accuracy in Process Performance Prediction. 418-436
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