Диссертация (1137084), страница 39
Текст из файла (страница 39)
—Pp. 371–384.56. Desel J., Reisig W. The Synthesis Problem of Petri Nets // Acta Informatica. — 1996. —Vol. 33, no. 4. — Pp. 297–315.57. Deriving Petri Nets from Finite Transition Systems / J. Cortadella, M. Kishinevsky, L. Lavagno, A. Yakovlev // IEEE Transactions on Computers. — 1998. — Vol.
47, no. 8. —Pp. 859–882.58. Process Mining: A Two-Step Approach to Balance Between Underfitting and Overfitting /W. M. P. van der Aalst, V. Rubin, H. M. W. Verbeek et al. // Software and Systems Modeling.— 2010. — Vol. 9, no. 1. — Pp. 87–111.17259. Solé M., Carmona J. Process Mining from a Basis of State Regions // Applications and Theory of Petri Nets, 31st International Conference, PETRI NETS 2010, Braga, Portugal, June21-25, 2010.
Proceedings. — Vol. 6128 of Lecture Notes in Computer Science. — SpringerVerlag, Berlin, 2010. — Pp. 226–245.60. Solé M., Carmona J. Rbminer: A Tool for Discovering Petri Nets from Transition Systems //Automated Technology for Verification and Analysis - 8th International Symposium, ATVA2010, Singapore, September 21-24, 2010.
Proceedings / Ed. by A. Bouajjani, Wei-Ngan Chin.— Vol. 6252 of Lecture Notes in Computer Science. — Springer-Verlag, Berlin, 2010. —Pp. 396–402.61. Solé Marc, Carmona Josep. Light Region-based Techniques for Process Discovery // Fundam.Inform. — 2011. — Vol. 113, no. 3-4. — Pp. 343–376.62. Solé Marc, Carmona Josep. Incremental Process Discovery // Trans. Petri Nets and OtherModels of Concurrency. — 2012.
— Vol. 5. — Pp. 221–242.63. van Zelst S. J., van Dongen B. F., van der Aalst W. M. P. ILP-Based Process DiscoveryUsing Hybrid Regions // ATAED@Petri Nets/ACSD. — Vol. 1371 of CEUR WorkshopProceedings. — CEUR-WS.org, 2015. — Pp. 47–61.64. Weijters A. J. M. M., van der Aalst W. M. P. Rediscovering Workflow Models from EventBased Data using Little Thumb // Integrated Computer-Aided Engineering. — 2003.
—Vol. 10, no. 2. — Pp. 151–162.65. Weijters A. J. M. M., van der Aalst W. M. P., Alves de Medeiros A. K. Process Miningwith the Heuristics Miner-algorithm. — BETA Working Paper Series, WP 166, EindhovenUniversity of Technology, Eindhoven, 2006.66. Leemans Sander J. J., Fahland Dirk, van der Aalst Wil M. P. Discovering Block-StructuredProcess Models from Event Logs - A Constructive Approach // Petri Nets. — Vol.
7927 ofLecture Notes in Computer Science. — Springer, 2013. — Pp. 311–329.67. Buijs J. C. A. M., van Dongen B. F., van der Aalst W. M. P. A Genetic Algorithm forDiscovering Process Trees // IEEE Congress on Evolutionary Computation (CEC 2012). —IEEE Computer Society, 2012. — Pp. 1–8.68.
Liesaputra Veronica, Yongchareon Sira, Chaisiri Sivadon. Efficient Process Model DiscoveryUsing Maximal Pattern Mining // BPM. — Vol. 9253 of Lecture Notes in Computer Science.— Springer, 2015. — Pp. 441–456.69. Constructs Competition Miner: Process Control-Flow Discovery of BP-Domain Constructs /David Redlich, Thomas Molka, Wasif Gilani et al. // BPM. — Vol. 8659 of Lecture Notes inComputer Science. — Springer, 2014. — Pp. 134–150.17370. Scalable Dynamic Business Process Discovery with the Constructs Competition Miner /David Redlich, Thomas Molka, Wasif Gilani et al.
// SIMPDA. — Vol. 1293 of CEURWorkshop Proceedings. — CEUR-WS.org, 2014. — Pp. 91–107.71. Soundness of Workflow Nets: Classification, Decidability, and Analysis / W. M. P. vander Aalst, K. M. van Hee, A. H. M. ter Hofstede et al. // Formal Aspects of Computing.— 2011. — Vol. 23, no. 3. — Pp. 333–363.72. van der Aalst W. M. P., Alves de Medeiros A. K., Weijters A. J. M. M. Genetic ProcessMining // Applications and Theory of Petri Nets 2005 / Ed.
by G. Ciardo, P. Darondeau.— Vol. 3536 of Lecture Notes in Computer Science. — Springer-Verlag, Berlin, 2005. —Pp. 48–69.73. Alves de Medeiros A. K., Weijters A. J. M. M., van der Aalst W. M. P. Genetic ProcessMining: An Experimental Evaluation // Data Mining and Knowledge Discovery.
— 2007. —Vol. 14, no. 2. — Pp. 245–304.74. Mining Process Models with Non-Free-Choice Constructs / L. Wen, W. M. P. van der Aalst,J. Wang, J. Sun // Data Mining and Knowledge Discovery. — 2007. — Vol. 15, no. 2. —Pp. 145–180.75. Discovering Colored Petri Nets From Event Logs / A.
Rozinat, R. S. Mans, M. Song, W. M. P.van der Aalst // International Journal on Software Tools for Technology Transfer. — 2008.— Vol. 10, no. 1. — Pp. 57–74.76. Process mining using BPMN: relating event logs and process models / Anna A. Kalenkova,Wil M. P. van der Aalst, Irina A. Lomazova, Vladimir A. Rubin // MoDELS. — ACM, 2016.— P. 123.77. Process mining using BPMN: relating event logs and process models / Anna A. Kalenkova,Wil M. P. van der Aalst, Irina A. Lomazova, Vladimir A. Rubin // Software and SystemModeling.
— 2017. — Vol. 16, no. 4. — Pp. 1019–1048.78. Beyond Tasks and Gateways: Discovering BPMN Models with Subprocesses, BoundaryEvents and Activity Markers / R. Conforti, M. Dumas, L. García-Bañuelos, M. La Rosa //Business Process Management. — Springer International Publishing, 2014. — Vol.
8659 ofLecture Notes in Computer Science. — Pp. 101–117.79. Maggi F. M., Jagadeesh Chandra Bose R. P., van der Aalst W. M. P. Efficient Discoveryof Understandable Declarative Process Models from Event Logs // International Conferenceon Advanced Information Systems Engineering (Caise 2012) / Ed. by J. Ralyte, X. Franch,S. Brinkkemper, S. Wrycza.
— Vol. 7328 of Lecture Notes in Computer Science. — SpringerVerlag, Berlin, 2012. — Pp. 270–285.17480. Di Ciccio Claudio, Mecella Massimo. A two-step fast algorithm for the automated discoveryof declarative workflows // CIDM. — IEEE, 2013. — Pp. 135–142.81. Maggi Fabrizio Maria, Slaats Tijs, Reijers Hajo.
The Automated Discovery of Hybrid Processes // BPM. — Vol. 8659 of Lecture Notes in Computer Science. — Springer, 2014. —Pp. 392–399.82. Mining local process models / Niek Tax, Natalia Sidorova, Reinder Haakma, WilM. P. van der Aalst // J. Innovation in Digital Ecosystems. — 2016. — Vol. 3, no. 2.— Pp. 183–196.83. Interest-Driven Discovery of Local Process Models / Niek Tax, Benjamin Dalmas, Natalia Sidorova et al. // CoRR. — 2017. — Vol. abs/1703.07116.84. Cardoso J. Process control-flow complexity metric: An empirical validation // IEEE International Conference on Services Computing (SCC 2006). — IEEE Computer Society, 2006.— Pp.
167–173.85. A Discourse on Complexity of Process Models / Jorge S. Cardoso, Jan Mendling, Gustaf Neumann, Hajo A. Reijers // Business Process Management Workshops. — Vol. 4103 of LectureNotes in Computer Science. — Springer, 2006. — Pp. 117–128.86. Cardoso Jorge. Approaches to Compute Workflow Complexity // The Role of Business Processes in Service Oriented Architectures. — Vol. 06291 of Dagstuhl Seminar Proceedings. —Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany, 2006.87.
Laue Ralf, Gruhn Volker. Complexity Metrics for Business Process Models // BIS. — Vol. 85of LNI. — GI, 2006. — Pp. 1–12.88. Cardoso Jorge. Business Process Quality Metrics: Log-Based Complexity of Workflow Patterns // OTM Conferences (1). — Vol. 4803 of Lecture Notes in Computer Science.
—Springer, 2007. — Pp. 427–434.89. Mendling J., Neumann G., van der Aalst W. M. P. Understanding the Occurrence of Errorsin Process Models Based on Metrics // Proceedings of the OTM Conference on Cooperativeinformation Systems (CoopIS 2007) / Ed. by F. Curbera, F. Leymann, M. Weske. — Vol. 4803of Lecture Notes in Computer Science. — Springer-Verlag, Berlin, 2007. — Pp. 113–130.90. Cardoso Jorge. Business Process Control-Flow Complexity: Metric, Evaluation, and Validation // Int. J.
Web Service Res. — 2008. — Vol. 5, no. 2. — Pp. 49–76.91. Analysis and Validation of Control-flow Complexity Measures with BPMN Process Models /Elvira Rolón Aguilar, Jorge S. Cardoso, Félix Garcı́a et al. // BMMDS/EMMSAD. — Vol. 29of Lecture Notes in Business Information Processing.
— Springer, 2009. — Pp. 58–70.17592. Mao Chengying. Control Flow Complexity Metrics for Petri Net-based Web Service Composition // JSW. — 2010. — Vol. 5, no. 11. — Pp. 1292–1299.93. van der Aalst Wil M. P., Adriansyah Arya, van Dongen Boudewijn. Replaying History onProcess Models for Conformance Checking and Performance Analysis // WIREs Data Miningand Knowledge Discovery. — 2012. — Vol. 2, no. 2. — Pp.
![](https://s.studizba.com/z.php?f=/templates/si/i/noavatar.png&w=100&h=100&t=1"){kind=avatar}
