On the discovery of explainable and accurate behavioral models for complex lowly-structured business processes

ICEIS 2015 - 17th International Conference on Enterprise Information Systems, Proceedings

Volumn 1, Issue , 2015, Pages 206-217

  Folino, Francesco ^a   Guarascio, Massimo ^a   Pontieri, Luigi ^a  

^a ICAR CNR   (Italy)

Author keywords

Business process intelligence; Data mining; Trace clustering; Workflow discovery

Indexed keywords

ECONOMIC AND SOCIAL EFFECTS; HEALTH;

BEHAVIORAL PROCESS; BUSINESS PROCESS INTELLIGENCE; CLUSTERING METHODS; ENVIRONMENTAL VARIABLES; STRUCTURED PROCESS; TRACE CLUSTERING; TWO-PHASE CLUSTERING; WORKFLOW DISCOVERY;

DATA MINING;

EID: 84939493756     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5220/0005470602060217     Document Type: Conference Paper

References (24)

1. CLUS: A predictive clustering system. http://dtai.cs. kuleuven. be/clus/.
2. Alves De Medeiros, A. K., Van Der Aalst, W. M. P., and Weijters, A. J. M. M. (2008). Quantifying process equivalence based on observed behavior. Data & Knowledge Engineering, 64(1):55-74.
3. Blockeel, H. and Raedt, L. D. (1998). Top-down induction of first-order logical decision trees. Artificial Intelligence, 101(1-2):285-297.
4. Bose, R. P. J. C. and Van Der Aalst, W. M. P. (2009a). Context aware trace clustering: Towards improving process mining results. In Proc. of SIAM International Conference on Data Mining, pages 401-412.
5. Bose, R. P. J. C. and Van Der Aalst, W. M. P. (2009b). Trace clustering based on conserved patterns: Towards achieving better process models. In Business Process Management Workshops, pages 170-181.
6. Buijs, J., Van Dongen, B., and Van Der Aalst, W. (2012). On the role of fitness, precision, generalization and simplicity in process discovery. In On the Move to Meaningful Internet Systems: OTM 2012, volume 7565, pages 305-322.
7. Cramer, H. (1999). Mathematical Methods of Statistics. Princeton University Press.
8. De Medeiros, A. A. (2006). Genetic Process Mining. Phd thesis, Eindhoven University of Technology.
9. De Weerdt, J., Van Den Broucke, S., Sand Vanthienen, J., and Baesens, B. (2013). Active trace clustering for improved process discovery. IEEE Trans, on Knowl. and Data Eng, 25(12):2708-2720.
10. Ferreira, D., Zacarias, M., Malheiros, M., and Ferreira, P. (2007). Approaching process mining with sequence clustering: Experiments and findings. In Proc. of 5th Int. Conf. on Business Process Management (BPM'07), pages 360-374.
11. Folino, F., Greco, G., Guzzo, A., and Pontieri, L. (2008). Discovering multi-perspective process models: The case of loosely-structured processes. In ICEIS 2008, Revised Selected Papers, pages 130-143.
12. Folino, F., Greco, G., Guzzo, A., and Pontieri, L. (2011). Mining usage scenarios in business processes: Outlier-aware discovery and run-time prediction. Data & Knowledge Engineering, 70(12):1005-1029.
13. Folino, F., Guarascio, M., and Pontieri, L. (2012). Discovering context-aware models for predicting business process performances. In Proc. of 20th Intl. Conf. on Cooperative Information Systems (CoopIS'12), pages 287-304.
14. Greco, G., Guzzo, A., Pontieri, L., and Saccà, D. (2006). Discovering expressive process models by clustering log traces. IEEE Trans. Knowl. and Data Eng., 18 (8).
15. Kunze, M., Weidlich, M., and Weske, M. (2011). Behavioral similarity: A proper metric. In Proc. of 9th Int. Conf. on Business Process Management (BPM'11), pages 166-181.
16. Rozinat, A. and Van Der Aalst, W. M. P. (2008). Conformance checking of processes based on monitoring real behavior. Information Systems, 33(1):64-95.
17. Song, M., Günther, C. W., and Van Der Aalst, W. (2008). Trace clustering in process mining. In Proc. of Business Process Management Workshops (BPI'08), pages 109-120.
18. Steeman, W. (2013). BPI challenge 2013, closed problems.
19. Van Der Aalst, W. (1998). The application of Petri nets to worflow management. Journal of Circuits, Systems, and Computers, 8(1):21-66.
20. Van Der Aalst, W., Adriansyah, A., and Van Dongen, B. (2011). Causal nets: a modeling language tailored towards process discovery. In Proc. of the 22nd Intl. Conf. on Concurrency Theory, CONCUR'11, pages 28-42, Berlin, Heidelberg. Springer-Verlag.
21. Van Der Aalst, W. M. P., Van Dongen, B. F., Herbst, J., Maruster, L., Schimm, G., and Weijters, A. J. M. M. (2003). Workflow mining: a survey of issues and approaches. Data & Knowledge Engineering, 47(2):237-267.
22. Weidlich, M., Polyvyanyy, A., Desai, N., Mendling, J., and Weske, M. (2011). Process compliance analysis based on behavioural profiles. Information Systems, 36(7):1009-1025.
23. Weijters, A. J. M. M. and Ribeiro, J. T. S. (2011). Flexible heuristics miner (FHM). In Proc. of IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2011), pages 310-317.
24. Weijters, A. J. M. M. and Van Der Aalst, W. M. P. (2003). Rediscovering workflow models from event-based data using Little Thumb. Integrated Computer-Aided Engineering, 10(2):151-162.