Extracting Event Data from Databases to Unleash Process Mining

Management for Professionals

Volumn Part F318, Issue , 2015, Pages 105-128

  van der Aalst, Wil M P ^a,b  

^a EINDHOVEN UNIVERSITY OF TECHNOLOGY   (Netherlands)

^b NATIONAL RESEARCH UNIVERSITY HIGHER SCHOOL OF ECONOMICS   (Russian Federation)

Author keywords

Business Process Management; Event Data; Event Occurrence; Near Field Communication; Process Mining

Indexed keywords

EID: 85162201766     PISSN: 21928096     EISSN: 2192810X     Source Type: Book Series    
DOI: 10.1007/978-3-319-14430-6_8     Document Type: Chapter

References (53)

1. Aalst, W. van der (2011). Process mining: Discovery, conformance and enhancement of business processes. Berlin: Springer.
2. Aalst, W. van der (2013a). Business process management: A comprehensive survey. ISRN Software Engineering, 1–37. doi:10.1155/2013/507984
3. Aalst, W. van der (2013b). Process cubes: Slicing, dicing, rolling up and drilling down event data for process mining. In M. Song, M. Wynn, & J. Liu (Eds.), Asia Pacific Conference on Business Process Management (AP-BPM 2013) (Lecture Notes in Business Information Processing, Vol. 159, pp. 1–22). Berlin: Springer.
4. Aalst, W. van der (2013c). Service mining: Using process mining to discover, check, and improve service behavior. IEEE Transactions on Services Computing, 6(4), 525–535.
5. Aalst, W. van der (2014). Data scientist: The engineer of the future. In K. Mertins, F. Benaben, R. Poler, & J. Bourrieres (Eds.), Proceedings of the I-ESA Conference (Enterprise Interopera-bility, Vol. 6, pp. 13–28). Berlin: Springer.
6. Aalst, W. van der, Adriansyah, A., & Dongen, B. van (2012). Replaying history on process models for conformance checking and performance analysis. WIREs Data Mining and Knowledge Discovery, 2(2), 182–192.
7. Aalst, W. van der, Barthelmess, P., Ellis, C., & Wainer, J. (2001). Proclets: A framework for lightweight interacting workflow processes. International Journal of Cooperative Information Systems, 10(4), 443–482.
8. Aalst, W. van der, Mooij, A., Stahl, C., & Wolf, K. (2009). Service interaction: Patterns, formalization, and analysis. In M. Bernardo, L. Padovani, & G. Zavattaro (Eds.), Formal methods for web services (Lecture Notes in Computer Science, Vol. 5569, pp. 42–88). Berlin: Springer.
9. Aalst, W. van der, Rubin, V., Verbeek, H., Dongen, B. van, Kindler, E., & Günther, C. (2010). Process mining: A two-step approach to balance between underfitting and overfitting. Software and Systems Modeling, 9(1), 87–111.
10. Aalst, W. van der, & Stahl, C. (2011). Modeling business processes: A petri net oriented approach. Cambridge, MA: MIT Press.
11. Aalst, W. van der, Weijters, A., & Maruster, L. (2004). Workflow mining: Discovering process models from event logs. IEEE Transactions on Knowledge and Data Engineering, 16(9), 1128–1142.
12. ACSI. (2013). Artifact-centric service interoperation (ACSI) project home page. Retrieved from www.acsi-project.eu
13. Adriansyah, A., Dongen, B. van, & Aalst, W. van der (2011a). Conformance checking using cost-based fitness analysis. In C. Chi & P. Johnson (Eds.), IEEE International Enterprise Computing Conference (EDOC 2011) (pp. 55–64). IEEE Computer Society Washington, DC, USA.
14. Adriansyah, A., Dongen, B., & Aalst, W. van der (2011b). Towards robust conformance checking. In M. Muehlen & J. Su (Eds.), BPM 2010 Workshops, Proceedings of the Sixth Workshop on Business Process Intelligence (BPI2010) (Lecture Notes in Business Information Processing, Vol. 66, pp. 122–133). Berlin: Springer.
15. Adriansyah, A., Sidorova, N., & Dongen, B. van (2011c). Cost-based fitness in conformance checking. In International Conference on Application of Concurrency to System Design (ACSD 2011) (pp. 57–66). IEEE Computer Society Washington, DC, USA.
16. Agrawal, R., Gunopulos, D., & Leymann, F. (1998). Mining process models from workflow logs. In Sixth International Conference on Extending Database Technology (Lecture Notes in Computer Science, Vol. 1377, pp. 469–483). Berlin: Springer.
17. Ana Karla Alves de Medeiros, Weijters, A., & Aalst, W. van der (2007). Genetic process mining: An experimental evaluation. Data Mining and Knowledge Discovery, 14(2), 245–304.
18. Barros, A., Decker, G., Dumas, M., & Weber, F. (2007). Correlation patterns in service-oriented architectures. In M. Dwyer & A. Lopes (Eds.), Proceedings of the 10th International Conference on Fundamental Approaches to Software Engineering (FASE 2007) (Lecture Notes in Computer Science, Vol. 4422, pp. 245–259). Berlin: Springer.
19. Bergenthum, R., Desel, J., Lorenz, R., & Mauser, S. (2007). Process mining based on regions of languages. In G. Alonso, P. Dadam, & M. Rosemann (Eds.), International Conference on Business Process Management (BPM 2007) (Lecture Notes in Computer Science, Vol. 4714, pp. 375–383). Berlin: Springer.
20. Brocke, J., & Rosemann, M. (Eds.). (2010). Handbook on business process management, international handbooks on information systems. Berlin: Springer.
21. Calders, T., Guenther, C., Pechenizkiy, M., & Rozinat, A. (2009). Using minimum description length for process mining. In ACM Symposium on Applied Computing (SAC 2009) (pp. 1451– 1455). New York, NY: ACM Press.
22. Carmona, J., & Cortadella, J. (2010). Process mining meets abstract interpretation. In J. Balcazar (Ed.), ECML/PKDD 210 (Lecture Notes in Artificial Intelligence, Vol. 6321, pp. 184–199). Berlin: Springer.
23. Carmona, J., Cortadella, J., & Kishinevsky, M. (2008). A region-based algorithm for discovering petri nets from event logs. In Business Process Management (BPM2008) (pp. 358–373). Berlin: Springer.
24. Chaudhuri, S., & Dayal, U. (1997). An overview of data warehousing and OLAP technology. ACM Sigmod Record, 26(1), 65–74.
25. Chen, P. (1976). The entity-relationship model: Towards a unified view of data. ACM Transactions on Database Systems, 1, 9–36.
26. Cohn, D., & Hull, R. (2009). Business artifacts: A data-centric approach to modeling business operations and processes. IEEE Data Engineering Bulletin, 32(3), 3–9.
27. Cook, J., & Wolf, A. (1998). Discovering models of software processes from event-based data. ACM Transactions on Software Engineering and Methodology, 7(3), 215–249.
28. Cook, J., & Wolf, A. (1999). Software process validation: Quantitatively measuring the correspondence of a process to a model. ACM Transactions on Software Engineering and Methodology, 8(2), 147–176.
29. Dumas, M., Marcello La Rosa, M., Mendling, J., & Reijers, H. (2013). Fundamentals of business process management. Berlin: Springer.
30. Fahland, D., Massimiliano de Leoni, Dongen, B. van, & Aalst, W. van der (2011a). Behavioral conformance of artifact-centric process models. In A. Abramowicz (Ed.), Business Information Systems (BIS 2011) (Lecture Notes in Business Information Processing, Vol. 87, pp. 37–49). Berlin: Springer.
31. Fahland, D., Massimiliano de Leoni, Dongen, B. van, & Aalst, W. van der (2011b). Many-to-many: Some observations on interactions in artifact choreographies. In D. Eichhorn, A. Koschmider, & H. Zhang (Eds.), Proceedings of the 3rd Central-European Workshop on Services and their Composition (ZEUS 2011), CEUR-WS.org, CEUR Workshop Proceedings (pp. 9–15).
32. Gaaloul, W., Gaaloul, K., Bhiri, S., Haller, A., & Hauswirth, M. (2009). Log-based transactional workflow mining. Distributed and Parallel Databases, 25(3), 193–240.
33. Goedertier, S., Martens, D., Vanthienen, J., & Baesens, B. (2009). Robust process discovery with artificial negative events. Journal of Machine Learning Research, 10, 1305–1340.
34. Günther, C., & Aalst, W. van der (2006). A generic import framework for process event logs. In J. Eder & S. Dustdar (Eds.), Business Process Management Workshops, Workshop on Business Process Intelligence (BPI 2006) (Lecture Notes in Computer Science, Vol. 4103, pp. 81–92). Berlin: Springer.
35. Hofstede, A. ter, Aalst, W. van der, Adams, M., & Russell, N. (2010). Modern business process automation: YAWL and its support environment. Berlin: Springer.
36. IEEE Task Force on Process Mining. (2011). Process mining manifesto. In BPM Workshops (Lecture Notes in Business Information Processing, Vol. 99). Berlin: Springer.
37. IEEE Task Force on Process Mining. (2013a). Process mining case studies. Retrieved from http://www.win.tue.nl/ieeetfpm/doku.php?id=shared:process_mining_case_studies
38. IEEE Task Force on Process Mining. (2013b). XES standard definition. Retrieved from www.xes-standard.org
39. Jagadeesh Chandra Bose, R.P., Mans, R., & Aalst, W. van der (2013). Wanna improve process mining results? It’s high time we consider data quality issues seriously. In B. Hammer, Z. Zhou, L. Wang, & N. Chawla (Eds.), IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2013) (pp. 127–134). Singapore: IEEE.
40. Montahari-Nezhad, H., Saint-Paul, R., Casati, F., & Benatallah, B. (2011). Event correlation for process discovery from web service interaction logs. VLBD Journal, 20(3), 417–444.
41. Munoz-Gama, J., & Carmona, J. (2010). A fresh look at precision in process conformance. In R. Hull, J. Mendling, & S. Tai (Eds.), Business Process Management (BPM 2010) (Lecture Notes in Computer Science, Vol. 6336, pp. 211–226). Berlin: Springer.
42. Munoz-Gama, J., & Carmona, J. (2011). Enhancing precision in process conformance: Stability, confidence and severity. In N. Chawla, I. King, & A. Sperduti (Eds.), IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2011) (pp. 184–191). Paris: IEEE.
43. OMG. (2009). Unified modeling language, infrastructure and superstructure (Version 2.2, OMG final adopted specification). http://www.omg.org/spec/UML/2.2/
44. Pauw, W., Lei, M., Pring, E., Villard, L., Arnold, M., & Morar, J. (2005). Web services navigator: Visualizing the execution of web services. IBM Systems Journal, 44(4), 821–845.
45. Reichert, M., & Weber, B. (2012). Enabling flexibility in process-aware information systems: Challenges, methods, technologies. Berlin: Springer.
46. Rosa, M. La, Reijers, H., Aalst, W. van der, Dijkman, R., Mendling, J., Dumas, M., et al. (2011). APROMORE: An advanced process model repository. Expert Systems with Applications, 38 (6), 7029–7040.
47. Rozinat, A., & Aalst, W. van der (2008). Conformance checking of processes based on monitoring real behavior. Information Systems, 33(1), 64–95.
48. Sole, M., & Carmona, J. (2010). Process mining from a basis of regions. In J. Lilius & W. Penczek (Eds.), Applications and Theory of Petri Nets 2010 (Lecture Notes in Computer Science, Vol. 6128, pp. 226–245). Berlin: Springer.
49. Verbeek, H., Buijs, J., Dongen, B. van, & Aalst, W. van der (2010). XES, XESame, and ProM 6. In P. Soffer & E. Proper (Eds.), Information systems evolution (Lecture Notes in Business Information Processing, Vol. 72, pp. 60–75). Berlin: Springer.
50. Weerdt, J., De Backer, M., Vanthienen, J., & Baesens, B. (2011). A robust f-measure for evaluating discovered process models. In N. Chawla, I. King, & A. Sperduti (Eds.), IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2011) (pp. 148–155). Paris: IEEE.
51. Weijters, A., & Aalst, W. van der (2003). Rediscovering workflow models from event-based data using little thumb. Integrated Computer-Aided Engineering, 10(2), 151–162.
52. Werf, J., Dongen, B. van, Hurkens, C., & Serebrenik, A. (2010). Process discovery using integer linear programming. Fundamenta Informaticae, 94, 387–412.
53. Weske, M. (2007). Business process management: Concepts, languages, architectures. Berlin: Springer.