Wil's References for the year 2019!

I try to update my webpage once per year and provide as many papers as possible. Enjoy reading! Click here to return to home page.

  1. W.M.P. van der Aalst. A Practitioner's Guide to Process Mining: Limitations of the Directly-Follows Graph. In International Conference on Enterprise Information Systems (Centeris 2019), volume 164 of Procedia Computer Science, pages 321-328. Elsevier, 2019.
  2. W.M.P. van der Aalst. Object-Centric Process Mining: Dealing With Divergence and Convergence in Event Data. In P.C. Ölveczky and G. Salaün, editors, Software Engineering and Formal Methods (SEFM 2019), volume 11724 of Lecture Notes in Computer Science, pages 3-25. Springer-Verlag, Berlin, 2019.
  3. E. González López de Murillas, H.A. Reijers, and W.M.P. van der Aalst. Connecting Databases With Process Mining: A Meta Model and Toolset. Software and System Modeling, 18(2):1209-1247, 2019.
  4. O. Hinz, W.M.P. van der Aalst, and C. Weinhardt. Blind Spots in Business and Information Systems Engineering. Business and Information Systems Engineering, 61(2):133-135, 2019.
  5. N. Tax, E. Alasgarov, N. Sidorova, R.Haakma, and W.M.P. van der Aalst. Generating Time-Based Label Refinements to Discover More Precise Process Models. Journal of Ambient Intelligence and Smart Environments, 11(2):165-182, 2019.
  6. N. Tax, N. Sidorova, and W.M.P. van der Aalst. Discovering More Precise Process Models From Event Logs By Filtering Out Chaotic Activities. Journal of Intelligent Information Systems, 52(1):107-139, 2019.
  7. W.M.P. van der Aalst. Structuring Behavior or Not, That is the Question. In K. Bergener, M. Rackers, and A. Stein, editors, The Art of Structuring, Bridging the Gap Between Information Systems Research and Practice, pages 221-226. Springer-Verlag, Berlin, 2019.
  8. R. Hähnle and W.M.P. van der Aalst, editors. International Conference on Fundamental Approaches to Software Engineering (FASE 2019), volume 11424 of Lecture Notes in Computer Science. Springer-Verlag, Berlin, 2019.
  9. W.M.P. van der Aalst. Interview in the 2019 Gartner Market Guide for Process Mining, Research Note G00387812 by M. Kerremans. www.gartner.com, 2019.
  10. S.J. van Zelst, A. Bolt, M. Hassani, B.F. van Dongen, and W.M.P. van der Aalst. Online Conformance Checking: Relating Event Streams to Process Models Using Prefix-Alignments. International Journal of Data Science and Analytics, 8:269-284, 2019.
  11. W.M.P. van der Aalst. Discovering Petri Nets: A Personal Journey. In W. Reisig and G. Rozenberg, editors, Carl Adam Petri: His Ideas, Personality, and Impact: Personal Stories, pages 3-9. Springer-Verlag, Berlin, 2019.
  12. A. Artale, D. Calvanese, M. Montali, and W.M.P. van der Aalst. Enriching Data Models with Behavioral Constraints. In S. Borgo, editor, Ontology Makes Sense (Essays in honor of Nicola Guarino), pages 257-277. IOS Press, 2019.
  13. W.M.P. van der Aalst, R. Bergenthum, and J. Carmona, editors. Proceedings of the International Workshop on Algorithms and Theories for the Analysis of Event Data (ATAED 2019), volume 2371 of CEUR Workshop Proceedings. CEUR-WS.org, 2019.
  14. L. Mannel and W.M.P. van der Aalst. Finding Complex Process-Structures by Exploiting the Token-Game. In S. Donatelli and S. Haar, editors, Applications and Theory of Petri Nets 2019, volume 11522 of Lecture Notes in Computer Science, pages 258-278. Springer-Verlag, Berlin, 2019.
  15. A. Berti and W.M.P. van der Aalst. Reviving Token-based Replay: Increasing Speed While Improving Diagnostics. In Proceedings of the International Workshop on Algorithms and Theories for the Analysis of Event Data (ATAED 2019), volume 2371 of CEUR Workshop Proceedings, pages 87-103. CEUR-WS.org, 2019.
  16. A. Berti, S.J. van Zelst, and W.M.P. van der Aalst. Process Mining for Python (PM4Py): Bridging the Gap Between Process and Data Science. CoRR, abs/1905.06169, 2019.
  17. M. Dees, M. de Leoni, W.M.P. van der Aalst, and H. Reijers. What if Process Predictions are not followed by Good Recommendations? CoRR, abs/1905.10173, 2019.
  18. M.S. Qafari and W.M.P. van der Aalst. Fairness-Aware Process Mining. CoRR, abs/1908.11451, 2019.
  19. A.F. Syring, N. Tax, and W.M.P. van der Aalst. Evaluating Conformance Measures in Process Mining using Conformance Propositions (Extended version). CoRR, abs/1909.02393, 2019.
  20. M. Pegoraro, M.S. Uysal, and W.M.P. van der Aalst. Discovering Process Models from Uncertain Event Data. CoRR, abs/1909.11567, 2019.
  21. M. Pegoraro and W.M.P. van der Aalst. Mining Uncertain Event Data in Process Mining. CoRR, abs/1910.00089, 2019.
  22. W.M.P. van der Aalst. Everything You Always Wanted to Know About Petri Nets, but Were Afraid to Ask. In T.T. Hildebrandt, B.F. van Dongen, M. Röglinger, and J. Mendling, editors, International Conference on Business Process Management (BPM 2019), volume 11675 of Lecture Notes in Computer Science, pages 3-9. Springer-Verlag, Berlin, 2019.
  23. A. Artale, A. Kovtunova, M. Montali, and W.M.P. van der Aalst. Modeling and Reasoning over Declarative Data-Aware Processes with Object-Centric Behavioral Constraints. In T.T. Hildebrandt, B.F. van Dongen, M. Röglinger, and J. Mendling, editors, International Conference on Business Process Management (BPM 2019), volume 11675 of Lecture Notes in Computer Science, pages 139-156. Springer-Verlag, Berlin, 2019.
  24. S.J.J. Leemans, A.F. Syring, and W.M.P. van der Aalst. Earth Movers' Stochastic Conformance Checking. In T.T. Hildebrandt, B.F. van Dongen, M. Röglinger, and J. Mendling, editors, Business Process Management Forum (BPM Forum 2019), volume 360 of Lecture Notes in Business Information Processing, pages 127-143. Springer-Verlag, Berlin, 2019.
  25. M. Fani Sani, A. Berti, S.J. van Zelst, and W.M.P. van der Aalst. Filtering Toolkit: Interactively Filter Event Logs to Improve the Quality of Discovered Models. In Proceedings of the BPM Demo Track at BPM 2019, volume 2420 of CEUR Workshop Proceedings, pages 134-138. CEUR-WS.org, 2019.
  26. A. Berti, S.J. van Zelst, and W.M.P. van der Aalst. PM4Py Web Services: Easy Development, Integration and Deployment of Process Mining Features in any Application Stack. In Proceedings of the BPM Demo Track at BPM 2019, volume 2420 of CEUR Workshop Proceedings, pages 174-183. CEUR-WS.org, 2019.
  27. C. Weinhardt, W.M.P. van der Aalst, and O. Hinz. Introducing Registered Reports to the Information Systems Community. Business and Information Systems Engineering, 61(4):381-384, 2019.
  28. M.L. van Eck, N. Sidorova, and W.M.P. van der Aalst. Guided Interaction Exploration and Performance Analysis in Artifact-Centric Process Models. Business and Information Systems Engineering, 61(6):649-663, 2019.
  29. A.A. Kalenkova, A. Burattin, M. de Leoni, W.M.P. van der Aalst, and A. Sperduti. Discovering High-Level BPMN Process Models From Event Data. Business Process Management Journal, 25(5):995-1019, 2019.
  30. A.F. Syring, N. Tax, and W.M.P. van der Aalst. Evaluating Conformance Measures in Process Mining Using Conformance Propositions. In M. Koutny, L. Pomello, and L.M. Kristensen, editors, Transactions on Petri Nets and Other Models of Concurrency (ToPNoC 14), volume 11970 of Lecture Notes in Computer Science, pages 192-221. Springer-Verlag, Berlin, 2019.
  31. M. Hassani, S.J. van Zelst, and W.M.P. van der Aalst. On the Application of Sequential Pattern Mining Primitives to Process Discovery: Overview, Outlook and Opportunity Identification. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 9(6):1-13, 2019.
  32. M. Dees, M. de Leoni, W.M.P. van der Aalst, and H. Reijers. What If Process Predictions Are Not Followed By Good Recommendations? In J. vom Brocke, J. Mendling, and M. Rosemann, editors, Proceedings of the Industry Forum at BPM 2019, volume 2428 of CEUR Workshop Proceedings, pages 61-72. CEUR-WS.org, 2019.
  33. W.M.P. van der Aalst, O. Hinz, and C. Weinhardt. Big Digital Platforms - Growth, Impact, and Challenges. Business and Information Systems Engineering, 61(6):645-648, 2019.
  34. C. Klinkmüller, A. Ponomarev, A.B. Tran, I. Weber, and W.M.P. van der Aalst. Mining Blockchain Processes: Extracting Process Mining Data from Blockchain Applications. In C. Di Ciccio, R. Gabryelczyk, L. García-Banuelos, T. Hernaus, R.Hull, M.I. Stemberger, A. Ko, and M. Staples, editors, Business Process Management: Blockchain and Central and Eastern Europe Forum (BPM 2019), volume 361 of Lecture Notes in Business Information Processing, pages 71-86. Springer-Verlag, Berlin, 2019. Winner of the Block Chain Forum best paper award.
  35. M.R. Harati Nik, W.M.P. van der Aalst, and M. Fani Sani. BIpm: Combining BI and Process Mining. In S. Hammoudi, C. Quix, and J. Bernardino, editors, International Conference on Data Science, Technology and Applications (DATA 2019), pages 123-128, Prague, Czech Republic, 2019. SciTePress.
  36. C. Liu, B.F. van Dongen, N. Assy, and W.M.P. van der Aalst. A General Framework to Identify Software Components from Execution Data. In E. Damiani, G. Spanoudakis, and L.A. Maciaszek, editors, International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2019), pages 234-241, Crete, Greece, 2019. SciTePress.
  37. G. Li, R.M. de Carvalho, and W.M.P. van der Aalst. A Model-based Framework to Automatically Generate Semi-real Data for Evaluating Data Analysis Techniques. In J. Filipe, M. Smialek, A. Brodsky, and S. Hammoudi, editors, International Conference on Enterprise Information Systems (ICEIS 2019), pages 213-220, Crete, Greece, 2019. SciTePress.
  38. M. Pegoraro and W.M.P. van der Aalst. Mining Uncertain Event Data in Process Mining. In J. Carmona, M. Jans, and M. La Rosa, editors, International Conference on Process Mining (ICPM 2019), pages 89-96, Aachen, Germany, 2019. IEEE Computer Society.
  39. V. Denisov, D. Fahland, and W.M.P. van der Aalst. Predictive Performance Monitoring of Material Handling Systems Using the Performance Spectrum. In J. Carmona, M. Jans, and M. La Rosa, editors, International Conference on Process Mining (ICPM 2019), pages 137-144, Aachen, Germany, 2019. IEEE Computer Society.
  40. J. Gao, S.J. van Zelst, X. Lu, and W.M.P. van der Aalst. Automated Robotic Process Automation: A Self-Learning Approach. In H. Panetto, C. Debruyne, M. Hepp, D. Lewis, C.A. Ardagna, and R. Meersman, editors, On the Move to Meaningful Internet Systems, International Conference on Cooperative Information Systems (CoopIS 2019), volume 11877 of Lecture Notes in Computer Science, pages 95-112. Springer-Verlag, Berlin, 2019.
  41. M.S. Qafari and W.M.P. van der Aalst. Fairness-Aware Process Mining. In H. Panetto, C. Debruyne, M. Hepp, D. Lewis, C.A. Ardagna, and R. Meersman, editors, On the Move to Meaningful Internet Systems, International Conference on Cooperative Information Systems (CoopIS 2019), volume 11877 of Lecture Notes in Computer Science, pages 182-192. Springer-Verlag, Berlin, 2019.
  42. M. Pourbafrani, S.J. van Zelst, and W.M.P. van der Aalst. Scenario-Based Prediction of Business Processes Using System Dynamics. In H. Panetto, C. Debruyne, M. Hepp, D. Lewis, C.A. Ardagna, and R. Meersman, editors, On the Move to Meaningful Internet Systems, International Conference on Cooperative Information Systems (CoopIS 2019), volume 11877 of Lecture Notes in Computer Science, pages 422-439. Springer-Verlag, Berlin, 2019.
  43. G. Li, R.M. de Carvalho, and W.M.P. van der Aalst. Object-Centric Behavioral Constraint Models: A Hybrid Model For Behavioral and Data Perspectives. In C.C. Hung and G.A. Papadopoulos, editors, ACM/SIGAPP Symposium on Applied Computing (SAC 2019), pages 48-56, Limassol, Cyprus, 2019. ACM Press, New York, NY, USA.
  44. W.M.P. van der Aalst. Fokus Prozesse: Von den Anfängen bis zur Verbesserung von Arbeitsabläufen in der Gesundheitsversorgung. In Wissensmanager: Das KMS Magazin für die Gesundheitswirtschaft (Herbst 2019), pages 4-10. Springer-Verlag, Berlin, 2019.
  45. W.M.P. van der Aalst. Using Process Mining to Removing Operational Friction in Shared Services (Blog Post SSON). www.ssonetwork.com, 2019.
  46. W.M.P. van der Aalst. Process Mining: Bridging Not Only Data and Processes, but Also Industry and Academia (Blog Post Celonis). www.celonis.com, 2019.
  47. W.M.P. van der Aalst, V. Batagelj, D. Ignatov, M. Khachay, V. Kuskova, A. Kutuzov, S. Kuznetsov, I.A. Lomazova, N. Loukachevitch, A. Napoli, P. Pardalos, M. Pelillo, A. Savchenko, and E. Tutubalina, editors. Proceedings of Analysis of Images, Social Networks and Texts (AIST 2019), volume 11832 of Lecture Notes in Computer Science. Springer-Verlag, Berlin, 2019.
  48. B. Depaire, J. De Smedt, M. Dumas, D. Fahland, A. Kumar, H. Leopold, M. Reichert, S. Rinderle-Ma, S. Schulte, S. Seidel, and W.M.P. van der Aalst, editors. Proceedings of the Dissertation Award, Doctoral Consortium, and Demonstration Track at BPM 2019, volume 2420 of CEUR Workshop Proceedings. CEUR-WS.org, 2019.
  49. W.M.P. van der Aalst, J. Carmona, T. Chatain, and B.F. van Dongen. A Tour in Process Mining: From Practice to Algorithmic Challenges. In M. Koutny, L. Pomello, and L.M. Kristensen, editors, Transactions on Petri Nets and Other Models of Concurrency (ToPNoC 14), volume 11970 of Lecture Notes in Computer Science, pages 1-35. Springer-Verlag, Berlin, 2019.
  50. W.M.P. van der Aalst. Lucent Process Models and Translucent Event Logs. Fundamenta Informaticae, 169(1-2):151-177, 2019.
  51. E. Benevento, P.M. Dixit, M. Fani Sani, D. Aloini, and W.M.P. van der Aalst. Evaluating the Effectiveness of Interactive Process Discovery in Healthcare: A Case Study. In C. Di Francescomarino, R. Dijkman, and U. Zdun, editors, Workshop Process-Oriented Data Science for Healthcare (PODS4H 2019), BPM 2019 Workshop Proceedings, volume 362 of Lecture Notes in Business Information Processing, pages 508-519. Springer-Verlag, Berlin, 2019.
  52. A. Pika, M. Wynn, S. Budiono, A. ter Hofstede, W.M.P. van der Aalst, and H.A. Reijers. Towards Privacy-Preserving Process Mining in Healthcare. In C. Di Francescomarino, R. Dijkman, and U. Zdun, editors, Workshop Process-Oriented Data Science for Healthcare (PODS4H 2019), BPM 2019 Workshop Proceedings, volume 362 of Lecture Notes in Business Information Processing, pages 483-495. Springer-Verlag, Berlin, 2019. Winner of the PODS4H 2019 best paper award.
  53. M. Rafiei and W.M.P. van der Aalst. Mining Roles From Event Logs While Preserving Privacy. In C. Di Francescomarino, R. Dijkman, and U. Zdun, editors, Workshop Security and Privacy-enhanced Business Process Management (SPBP 2019), BPM 2019 Workshop Proceedings, volume 362 of Lecture Notes in Business Information Processing, pages 676-689. Springer-Verlag, Berlin, 2019.
  54. C.Y. Li, S. van Zelst, and W.M.P. van der Aalst. A Generic Approach for Process Performance Analysis using Bipartite Graph Matching. In C. Di Francescomarino, R. Dijkman, and U. Zdun, editors, Workshop on Business Process Intelligence (BPI 2019), BPM 2019 Workshop Proceedings, volume 362 of Lecture Notes in Business Information Processing, pages 199-211. Springer-Verlag, Berlin, 2019.
  55. L.L. Mannel and W.M.P. van der Aalst. Finding Uniwired Petri Nets Using eST-Miner. In C. Di Francescomarino, R. Dijkman, and U. Zdun, editors, Workshop on Business Process Intelligence (BPI 2019), BPM 2019 Workshop Proceedings, volume 362 of Lecture Notes in Business Information Processing, pages 224-237. Springer-Verlag, Berlin, 2019.
  56. M. Pegoraro, M.S. Uysal, and W.M.P. van der Aalst. Discovering Process Models from Uncertain Event Data. In C. Di Francescomarino, R. Dijkman, and U. Zdun, editors, Workshop on Business Process Intelligence (BPI 2019), BPM 2019 Workshop Proceedings, volume 362 of Lecture Notes in Business Information Processing, pages 238-249. Springer-Verlag, Berlin, 2019.
  57. M. Fani Sani, S.J. van Zelst, and W.M.P. van der Aalst. The Impact of Event Log Subset Selection on the Performance of Process Discovery Algorithms. In T. Welzer and J. Eder, editors, New Trends in Databases and Information Systems, ADBIS 2019 Short Papers, volume 1064 of Communications in Computer and Information Science, pages 391-404. Springer-Verlag, Berlin, 2019.