Data-driven process discovery - Revealing conditional infrequent behavior from event logs

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 10253 LNCS, Issue , 2017, Pages 545-560

  Mannhardt, Felix ^a   De Leoni, Massimiliano ^a   Reijers, Hajo A ^a,b   Van Der Aalst, Wil M P ^a  

^a EINDHOVEN UNIVERSITY OF TECHNOLOGY   (Netherlands)

^b VU UNIVERSITY AMSTERDAM   (Netherlands)

Author keywords

Event logs; Noise; Process discovery; Process mining; Rules

Indexed keywords

FILTRATION; INFORMATION SYSTEMS; SYSTEMS ENGINEERING;

EVENT LOGS; NOISE; PROCESS DISCOVERY; PROCESS MINING; RULES;

HEURISTIC METHODS;

EID: 85021250616     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-59536-8_34     Document Type: Conference Paper

References (30)

1. Davies, I., Green, P., Rosemann, M., Indulska, M., Gallo, S.: How do practitioners use conceptual modeling in practice? Data Knowl. Eng. 58(3), 358–380 (2006)
2. van der Aalst, W.M.P.: Process Mining - Data Science in Action, 2nd edn. Springer, Heidelberg (2016)
3. Weerdt, J.D., Backer, M.D., Vanthienen, J., Baesens, B.: A multi-dimensional quality assessment of state-of-the-art process discovery algorithms using real-life event logs. Inf. Syst. 37(7), 654–676 (2012)
4. Suriadi, S., Andrews, R., ter Hofstede, A., Wynn, M.: Event log imperfection patterns for process mining: towards a systematic approach to cleaning event logs. Inf. Syst. 64, 132–150 (2017)
5. van der Aalst, W.M.P., Weijters, T., Maruster, L.: Workflow mining: discovering process models from event logs. IEEE Trans. Knowl. Data Eng. 16(9), 1128–1142 (2004)
6. Carmona, J., Cortadella, J., Kishinevsky, M.: A region-based algorithm for discovering petri nets from event logs. In: Dumas, M., Reichert, M., Shan, M.-C. (eds.) BPM 2008. LNCS, vol. 5240, pp. 358–373. Springer, Heidelberg (2008). doi:10.1007/978-3-540-85758-7_26
7. Günther, C.W., van der Aalst, W.M.P.: Fuzzy mining – adaptive process simplification based on multi-perspective metrics. In: Alonso, G., Dadam, P., Rosemann, M. (eds.) BPM 2007. LNCS, vol. 4714, pp. 328–343. Springer, Heidelberg (2007). doi:10.1007/978-3-540-75183-0_24
8. Weijters, A., Ribeiro, J.: Flexible heuristics miner (FHM). In: CIDM, pp. 310–317. IEEE (2011)
9. Leemans, S.J.J., Fahland, D., van der Aalst, W.M.P.: Discovering block-structured process models from event logs containing infrequent behaviour. In: Lohmann, N., Song, M., Wohed, P. (eds.) BPM 2013. LNBIP, vol. 171, pp. 66–78. Springer, Cham (2014). doi:10.1007/978-3-319-06257-0_6
10. Liesaputra, V., Yongchareon, S., Chaisiri, S.: Efficient process model discovery using maximal pattern mining. In: Motahari-Nezhad, H.R., Recker, J., Weidlich, M. (eds.) BPM 2015. LNCS, vol. 9253, pp. 441–456. Springer, Cham (2015). doi:10.1007/978-3-319-23063-4_29
11. Goedertier, S., Martens, D., Vanthienen, J., Baesens, B.: Robust process discovery with artificial negative events. J. Mach. Learn. Res. 10, 1305–1340 (2009)
12. Ponce-de-León, H., Carmona, J., vanden Broucke, S.K.L.M.: Incorporating negative information in process discovery. In: Motahari-Nezhad, H.R., Recker, J., Weidlich, M. (eds.) BPM 2015. LNCS, vol. 9253, pp. 126–143. Springer, Cham (2015). doi:10.1007/978-3-319-23063-4_8
13. Buijs, J., van Dongen, B.F., van der Aalst, W.M.P.: A genetic algorithm for discovering process trees. In: IEEE Congress on Evolutionary Computation, pp. 1–8. IEEE (2012)
14. Rembert, A.J., Omokpo, A., Mazzoleni, P., Goodwin, R.T.: Process discovery using prior knowledge. In: Basu, S., Pautasso, C., Zhang, L., Fu, X. (eds.) ICSOC 2013. LNCS, vol. 8274, pp. 328–342. Springer, Heidelberg (2013). doi:10.1007/978-3-642-45005-1_23
15. Bellodi, E., Riguzzi, F., Lamma, E.: Statistical relational learning for workflow mining. Intell. Data Anal. 20(3), 515–541 (2016)
16. Ghionna, L., Greco, G., Guzzo, A., Pontieri, L.: Outlier detection techniques for process mining applications. In: An, A., Matwin, S., Raś, Z.W., Ślęzak, D. (eds.) ISMIS 2008. LNCS, vol. 4994, pp. 150–159. Springer, Heidelberg (2008). doi:10.1007/978-3-540-68123-6_17
17. Conforti, R., Rosa, M.L., ter Hofstede, A.H.M.: Filtering out infrequent behavior from business process event logs. IEEE Trans. Knowl. Data Eng. 29(2), 300–314 (2017)
18. Rozinat, A., Mans, R.S., Song, M., van der Aalst, W.M.P.: Discovering simulation models. Inf. Syst. 34(3), 305–327 (2009)
19. de Leoni, M., van der Aalst, W.M.P.: Data-aware process mining: discovering decisions in processes using alignments. In: SAC 2013, pp. 1454–1461. ACM (2013)
20. Bazhenova, E., Buelow, S., Weske, M.: Discovering decision models from event logs. In: Abramowicz, W., Alt, R., Franczyk, B. (eds.) BIS 2016. LNBIP, vol. 255, pp. 237–251. Springer, Cham (2016). doi:10.1007/978-3-319-39426-8_19
21. Schönig, S., Ciccio, C., Maggi, F.M., Mendling, J.: Discovery of multi-perspective declarative process models. In: Sheng, Q.Z., Stroulia, E., Tata, S., Bhiri, S. (eds.) ICSOC 2016. LNCS, vol. 9936, pp. 87–103. Springer, Cham (2016). doi:10.1007/978-3-319-46295-0_6
22. van der Aalst, W., Adriansyah, A., van Dongen, B.: Causal nets: a modeling language tailored towards process discovery. In: Katoen, J.-P., König, B. (eds.) CONCUR 2011. LNCS, vol. 6901, pp. 28–42. Springer, Heidelberg (2011). doi:10.1007/978-3-642-23217-6_3
23. Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann, Burlington (1993)
24. Cohen, J.: A coefficient of agreement for nominal scales. Educ. Psychol. Measur. 20(1), 37–46 (1960)
25. Ben-David, A.: About the relationship between ROC curves and Cohen’s kappa. Eng. Appl. Artif. Intell. 21(6), 874–882 (2008)
26. vanden Broucke, S.: Advances in process mining: artificial negative events and othertechniques. Ph.D. thesis, KU Leuven (2014)
27. Dijkman, R., Dumas, M., García-Bañuelos, L.: Graph matching algorithms for business process model similarity search. In: Dayal, U., Eder, J., Koehler, J., Reijers, H.A. (eds.) BPM 2009. LNCS, vol. 5701, pp. 48–63. Springer, Heidelberg (2009). doi:10.1007/978-3-642-03848-8_5
28. de Leoni, M., Mannhardt, F.: Road traffic fine management process (2015). doi:10.4121/uuid:270fd440-1057-4fb9-89a9-b699b47990f5
29. Mannhardt, F., de Leoni, M., Reijers, H.A., van der Aalst, W.M.P.: Balanced multiperspective checking of process conformance. Computing 98(4), 407–437 (2016)
30. Augusto, A., Conforti, R., Dumas, M., Rosa, M., Bruno, G.: Automated discovery of structured process models: discover structured vs. discover and structure. In: Comyn-Wattiau, I., Tanaka, K., Song, I.-Y., Yamamoto, S., Saeki, M. (eds.) ER 2016. LNCS, vol. 9974, pp. 313–329. Springer, Cham (2016). doi:10.1007/978-3-319-46397-1_25