Mining conditional partial order graphs from event logs

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

Volumn 9930 LNCS, Issue , 2016, Pages 114-136

  Mokhov, Andrey ^a   Carmona, Josep ^b   Beaumont, Jonathan ^a  

^a NEWCASTLE UNIVERSITY   (United Kingdom)

^b UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING;

COMPACT REPRESENTATION; CONTROL FLOWS; CURRENT LIMITATION; EVENT LOGS; PARTIAL ORDER; PROCESS MINING; PROCESS MODELING; REPRESENTATION OF EVENTS;

PETRI NETS;

EID: 84988384027     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-662-53401-4_6     Document Type: Conference Paper

References (42)

1. van der Aalst, W.: Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer, Heidelberg (2011)
2. The ProM framework homepage (2010). http://www.promtools.org/
3. Song, M., van der Aalst, W.M.P.: Supporting process mining by showing events at a glance. In: Proceedings of Annual Workshop on Information Technologies and Systems (WITS), pp. 139-145 (2007)
4. Mokhov, A.: Conditional partial order graphs. Ph.D. thesis, Newcastle University (2009)
5. Mokhov, A., Khomenko, V.: Algebra of parameterised graphs. ACM Trans. Embed. Comput. Syst. (TECS) 13(4s), 143 (2014)
6. Mokhov, A., Carmona, J.: Event log visualisation with conditional partial order graphs: from control flow to data. In: Proceedings of the International Workshop on Algorithms and Theories for the Analysis of Event Data, ATAED, Brussels, Belgium, 22-23 June, pp. 16-30 (2015)
7. The Workcraft framework homepage (2009). http://www.workcraft.org
8. The PGminer tool repository (2015). https://github.com/tuura/process-mining
9. van der Aalst, W.M.P., Weijters, T., Maruster, L.: Workflow mining: discovering process models from event logs. IEEE TKDE 16(9), 1128-1142 (2004)
10. Buijs, J.C.A.M., van Dongen, B.F., van der Aalst, W.M.P.: A genetic algorithm for discovering process trees. In: Proceedings of the IEEE Congress on Evolutionary Computation, CEC, Brisbane, Australia, 10-15 June, pp. 1-8 (2012)
11. Leemans, S.J.J., Fahland, D., van der Aalst, W.M.P.: Discovering block-structured process models from event logs - a constructive approach. In: Colom, J.-M., Desel, J. (eds.) PETRI NETS 2013. LNCS, vol. 7927, pp. 311-329. Springer, Heidelberg (2013)
12. Carmona, J., Cortadella, J., Kishinevsky, M.: New region-based algorithms for deriving bounded Petri nets. IEEE Trans. Comput. 59(3), 371-384 (2010)
13. Bergenthum, R., Desel, J., Lorenz, R., Mauser, S.: Synthesis of Petri nets from finite partial languages. Fundam. Inf. 88(4), 437-468 (2008)
14. Mokhov, A., Sokolov, D., Yakovlev, A.: Adapting asynchronous circuits to operating conditions by logic parametrisation. In: IEEE International Symposium on Asynchronous Circuits and Systems (ASYNC), pp. 17-24. IEEE (2012)
15. Mokhov, A., Rykunov, M., Sokolov, D., Yakovlev, A.: Design of processors with reconfigurable microarchitecture. J. Low Power Electron. Appl. 4(1), 26-43 (2014)
16. de Micheli, G.: Synthesis and Optimization of Digital Circuits. McGraw-Hill Higher Education, New York (1994)
17. Wegener, I.: The complexity of Boolean functions. Johann Wolfgang Goethe-Universitat (1987)
18. Ponce-de-León, H., Mokhov, A.: Building bridges between sets of partial orders. In: Dediu, A.-H., Formenti, E., Martın-Vide, C., Truthe, B. (eds.) LATA 2015. LNCS, vol. 8977, pp. 145-160. Springer, Heidelberg (2015)
19. Nielsen, M., Plotkin, G., Winskel, G.: Petri nets, event structures and domains, part I. Theor. Comput. Sci. 13, 85-108 (1981)
20. McMillan, K.: Using unfoldings to avoid the state explosion problem in the verification of asynchronous circuits. In: Proceedings of Computer Aided Verification Conference (CAV), vol. 663, p. 164 (1992)
21. Mokhov, A., Alekseyev, A., Yakovlev, A.: Encoding of processor instruction sets with explicit concurrency control. IET Comput. Digital Tech. 5(6), 427-439 (2011)
22. de Gennaro, A., Stankaitis, P., Mokhov, A.: A heuristic algorithm for deriving compact models of processor instruction sets. In: International Conference on Application of Concurrency to System Design (ACSD) (2015)
23. Villa, T., Kam, T., Brayton, R.K., Sangiovanni-Vincentelli, A.L.: Synthesis of Finite State Machines: Logic Optimization. Springer, New York (2012)
24. Solé, M., Carmona, J.: Light region-based techniques for process discovery. Fundam. Inf. 113(3-4), 343-376 (2011)
25. van der Werf, J.M.E.M., van Dongen, B.F., Hurkens, C.A.J., Serebrenik, A.: Process discovery using integer linear programming. In: ATPN, pp. 368-387 (2008)
26. 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)
27. Weijters, A.J.M.M., van der Aalst, W.M.P., Alves de Medeiros, A.K.: Process mining with the heuristics miner-algorithm. Technical Report WP 166, BETA Working Paper Series, Eindhoven University of Technology (2006)
28. Haar, S., Kern, C., Schwoon, S.: Computing the reveals relation in occurrence nets. Theor. Comput. Sci. 493, 66-79 (2013)
29. Mitchell, T.M.: Machine Learning. McGraw Hill Series in Computer Science. McGraw-Hill, New York (1997)
30. Quinlan, J.R.: Induction of decision trees. Mach. Learn. 1(1), 81-106 (1986)
31. Cortes, C., Vapnik, V.: Support-vector networks. Mach. Learn. 20(3), 273-297 (1995)
32. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA data mining software: an update. ACM SIGKDD Explor. Newsl. 11(1), 10-18 (2009)
33. Poliakov, I., Sokolov, D., Mokhov, A.: Workcraft: a static data flow structure editing, visualisation and analysis tool. In: Kleijn, J., Yakovlev, A. (eds.) ICATPN 2007. LNCS, vol. 4546, pp. 505-514. Springer, Heidelberg (2007)
34. The Scenco tool website (2015). http://www.workcraft.org/scenco
35. The Weka tool website (2015). http://www.cs.waikato.ac.nz/ml/weka
36. Marlow, S., et al.: Haskell 2010 language report (2010). http://www.haskell.org/
37. ActiTraC: Active Trace Clustering (2014). http://www.processmining.be/actitrac/
38. Dumas, M., Garcıa-Bañuelos, L.: Process mining reloaded: event structures as a unified representation of process models and event logs. In: Devillers, R., Valmari, A. (eds.) PETRI NETS 2015. LNCS, vol. 9115, pp. 33-48. Springer, Heidelberg (2015)
39. Jagadeesh Chandra Bose, R.P., van der Aalst, W.M.P.: Process diagnostics using trace alignment: opportunities, issues, and challenges. Inf. Syst. 37(2), 117-141 (2012)
40. 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)
41. Lu, X., Mans, R., Fahland, D., van der Aalst, W.M.P.: Conformance checking in healthcare based on partially ordered event data. In: Proceedings of the IEEE Emerging Technology and Factory Automation, ETFA, Barcelona, Spain, 16-19 September, pp. 1-8 (2014)
42. Leemans, M., van der Aalst, W.M.P.: Discovery of frequent episodes in event logs. In: Ceravolo, P., Russo, B., Accorsi, R. (eds.) SIMPDA 2014. LNBIP, vol. 237, pp. 1-31. Springer, Heidelberg (2014)