Control-flow discovery from event streams

Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014

Volumn , Issue , 2014, Pages 2420-2427

  Burattin, Andrea ^a   Sperduti, Alessandro ^a   Van Der Aalst, Wil M P ^b  

^a UNIVERSITY OF PADOVA   (Italy)

^b EINDHOVEN UNIVERSITY OF TECHNOLOGY   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

BUDGET CONTROL; DATA STREAMS; MINERS;

BUSINESS PROCESS MODEL; CONTROL FLOWS; DISCOVERY ALGORITHM; EVENT STREAMS; PROCESS MINING; REAL DATA SETS; RESEARCH FIELDS; SLIDING WINDOW-BASED;

DATA MINING;

EID: 84908565982     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2014.6900341     Document Type: Conference Paper

References (30)

1. W. M. P. van der Aalst, "Process Discovery: Capturing the Invisible," IEEE Computational Intelligence Magazine, vol. 5, no. 1, pp. 28-41, 2010.
2. -, Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer, 2011.
3. J. E. Cook, "Process discovery and validation through event-data analysis," PhD Thesis, University of Colorado, 1996.
4. R. Agrawal, D. Gunopulos, and F. Leymann, "Mining Process Models from Workflow Logs," in Proc. of EDBT, Jan. 1998, pp. 469-483.
5. J. Herbst, "A Machine Learning Approach to Workflow Management," in Proc. of ECML, vol. 1810, 2000, pp. 183-194.
6. S.-Y. Hwang and W.-S. Yang, "On the discovery of process models from their instances," Decision Support Systems, vol. 34, no. 1, pp. 41-57, 2002.
7. G. Schimm, "Process Miner-A Tool for Mining Process Schemes from Event-Based Data," in Proc. of JELIA. Springer, 2002, pp. 525-528.
8. T. Murata, "Petri nets: Properties, analysis and applications," Proc. of the IEEE, vol. 77, no. 4, pp. 541-580, 1989.
9. W. M. P. van der Aalst and B. van Dongen, "Discovering Workflow Performance Models from Timed Logs," in Proc. of EDCIS. Springer, 2002, pp. 45-63.
10. N. Russell, A. H. ter Hofstede, W. M. P. van der Aalst, and N. Mulyar, "Workflow Control-flow Patterns: A Revised View," BPM Center Report BPM-06-22, BPMcenter. org, 2006.
11. J. Manyika, M. Chui, B. Brown, J. Bughin, R. Dobbs, C. Roxburgh, and A. Hung Byers, "Big Data: The Next Frontier for Innovation, Competition, and Productivity," McKinsey Global Institute, Tech. Rep. June, 2011.
12. L. Golab and M. T. Ö zsu, "Issues in Data Stream Management," ACM SIGMOD Record, vol. 32, no. 2, pp. 5-14, Jun. 2003.
13. C. Aggarwal, Data Streams: Models and Algorithms, ser. Advances in Database Systems. Boston, MA: Springer US, 2007, vol. 31.
14. A. Bifet, G. Holmes, R. Kirkby, and B. Pfahringer, "MOA: Massive Online Analysis Learning Examples," The Journal of Machine Learning Research, vol. 11, pp. 1601-1604, 2010.
15. G. Widmer and M. Kubat, "Learning in the Presence of Concept Drift and Hidden Contexts," Machine Learning, vol. 23, no. 1, pp. 69-101, 1996.
16. M. M. Gaber, A. Zaslavsky, and S. Krishnaswamy, "Mining Data Streams: A Review," ACM Sigmod Record, vol. 34, no. 2, pp. 18-26, Jun. 2005.
17. J. Gama, Knowledge Discovery from Data Streams. Chapman and Hall/CRC, May 2010.
18. W. M. P. van der Aalst and T. A. J. M. M. Weijters, "Rediscovering Workflow Models from Event-based Data Using Little Thumb," Integrated Computer-Aided Eng., vol. 10, no. 2, pp. 151-162, 2003.
19. E. Kindler, V. Rubin, and W. Schafer, "Incremental Workflow Mining for Process Flexibility," in Proc. of BPMDS, 2006, pp. 178-187.
20. A. C. Kalsing, G. S. do Nascimento, C. Iochpe, and L. H. Thom, "An Incremental Process Mining Approach to Extract Knowledge from Legacy Systems," in Proc. of EDOC, Oct. 2010, pp. 79-88.
21. R. P. J. C. Bose, W. M. P. van der Aalst, I. Ž liobaite, and M. Pechenizkiy, "Handling Concept Drift in Process Mining," in Proc. of CAiSE. Springer, 2011, pp. 391-405.
22. F. M. Maggi, A. Burattin, M. Cimitile, and A. Sperduti, "Online Process Discovery to Detect Concept Drifts in LTL-Based Declarative Process Models," in Proc. of CoopIS. Springer, 2013, pp. 94-111.
23. W. M. P. van der Aalst, T. A. J. M. M. Weijters, and A. K. A. de Medeiros, "Process Mining with the Heuristics Miner-Algorithm," BETA Working Paper Series, WP 166, Eindhoven University of Technology, Eindhoven, 2006.
24. N. Schweikardt, "Short-Entry on One-Pass Algorithms," in Encyclopedia of Database Systems, L. Liu and M. T. Ö szu, Eds. Springer, 2009, pp. 1948-1949.
25. G. S. Manku and R. Motwani, "Approximate Frequency Counts over Data Streams," in Proc. of VLDB. Hong Kong, China: Morgan Kaufmann, 2002, pp. 346-357.
26. G. Da San Martino, N. Navarin, and A. Sperduti, "A Lossy Counting Based Approach for Learning on Streams of Graphs on a Budget," in Proc. of IJCAI. AAAI Press, 2012, pp. 1294-1301.
27. F. Aiolli, A. Burattin, and A. Sperduti, "A Business Process Metric Based on the Alpha Algorithm Relations," in Proc. of BPI. Springer, 2011.
28. A. Burattin and A. Sperduti, "PLG: A Framework for the Generation of Business Process Models and their Execution Logs," in Proc. of BPI. Springer, 2010, pp. 214-219.
29. A. Adriansyah, B. van Dongen, and W. M. P. van der Aalst, "Conformance Checking Using Cost-Based Fitness Analysis," in Proc. of EDOC. IEEE, Aug. 2011, pp. 55-64.
30. J. Munoz Gama and J. Carmona, "A fresh look at Precision in Process Conformance," in Proc. of BPM. Springer, 2010, pp. 211-226.