Detecting deviating behaviors without models

Lecture Notes in Business Information Processing

Volumn 256, Issue , 2016, Pages 126-139

  Lu, Xixi ^a   Fahland, Dirk ^a   van den Biggelaar, Frank J H M ^b   van der Aalst, Wil M P ^a  

^a EINDHOVEN UNIVERSITY OF TECHNOLOGY   (Netherlands)

^b MAASTRICHT UNIVERSITY MEDICAL CENTER   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

ENTERPRISE RESOURCE MANAGEMENT;

ACCURATE MODELING; BUSINESS PROCESS; DEVIATION DETECTION; NORMATIVE MODELS; NORMATIVE PROCESS; PROCESS EXECUTION; PROCESS INSTANCES; PROCESS-INSTANCE LEVEL;

ADMINISTRATIVE DATA PROCESSING;

EID: 84979583917     PISSN: 18651348     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-319-42887-1_11     Document Type: Conference Paper

References (13)

1. van der Aalst, W.M.P., Adriansyah, A., van Dongen, B.F.: Replaying history on process models for conformance checking and performance analysis. Wiley Interdisc. Rev. Data Min. Knowl. Disc. 2(2), 182–192 (2012)
2. Bose, R., van der Aalst, W.M.P.: Context aware trace clustering: towards improving process mining results. In: Proceedings of the SIAM International Conference on Data Mining, SDM 2009, Sparks, Nevada, USA, 30 April–2 May, pp. 401–412 (2009)
3. Bose, R.P.J.C., van der Aalst, W.M.P.: Process diagnostics using trace alignment: opportunities, issues, and challenges. Inf. Syst. 37(2), 117–141 (2012)
4. Carmona, J., Cortadella, J.: Process discovery algorithms using numerical abstract domains. IEEE Trans. Knowl. Data Eng. 26(12), 3064–3076 (2014)
5. DeWeerdt, J., vanden Broucke, S.K.L.M., Vanthienen, J., Baesens, B.: Active trace clustering for improved process discovery. IEEE Trans. Knowl. Data Eng. 25(12), 2708–2720 (2013)
6. Fahland, D., van der Aalst, W.M.P.: Simplifying discovered process models in a controlled manner. Inf. Syst. 38(4), 585–605 (2013)
7. Ghionna, L., Greco, G., Guzzo, A., Pontieri, L.: Outlier detection techniques for process mining applications. In: An, A., Matwin, S., Rás, Z.W., Ślęzak, D. (eds.) ISMIS 2008. LNCS (LNAI), vol. 4994, pp. 150–159. Springer, Heidelberg (2008)
8. 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 Workshops. LNBIP, vol. 171, pp. 66–78. Springer, Heidelberg (2014)
9. Lu, X., Fahland, D., van der Aalst, W.M.P.: Conformance checking based on partially ordered event data. In: Fournier, F., Mendling, J. (eds.) BPM 2014 Workshops. LNBIP, vol. 202, pp. 75–88. Springer, Heidelberg (2015)
10. Nguyen, H., Dumas, M., La Rosa, M., Maggi, F.M., Suriadi, S.: Mining business process deviance: a quest for accuracy. In: Meersman, R., Panetto, H., Dillon, T., Missikoff, M., Liu, L., Pastor, O., Cuzzocrea, A., Sellis, T. (eds.) OTM 2014. LNCS, vol. 8841, pp. 436–445. Springer, Heidelberg (2014)
11. Rebuge, A., Ferreira, D.: Business process analysis in healthcare environments: a methodology based on process mining. Inf. Syst. 37(2), 99–116 (2012)
12. Suriadi, S., Wynn, M.T., Ouyang, C., ter Hofstede, A.H.M., van Dijk, N.J.: Understanding process behaviours in a large insurance company in Australia: a case study. In: Salinesi, C., Norrie, M.C., Pastor, Ó. (eds.) CAiSE 2013. LNCS, vol. 7908, pp. 449–464. Springer, Heidelberg (2013)
13. Yang, W., Hwang, S.: A process-mining framework for the detection of healthcare fraud and abuse. Expert Syst. Appl. 31(1), 56–68 (2006)