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Optimizing Business Processes Using Process Mining Techniques

Tati Pati Sai Krishna, Dr. Emmanuel M

Abstract


Organizations use business process modelling software to develop their functioning systems. The business process management software has helped to integrate the various modules of an organization in order to complete task/tasks. More recently, the work for providing an optimum solution is underway. Process mining techniques can be used to monitor the software development process. Business processes leave their footprints in event logs and recent research in process mining  make it possible to discover and optimize business processes based on the analysis of such logs. These logs can be used for knowledge mining and hence can be used to provide an optimal solution regarding the generation of the process.


Keywords


Business Process Management, Conformance Checking, Task Operation Model

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References


A.J.M.M Weijters, W.M.P. Van der Aalst and A.K. Alves de Medeiros, “Process mining with the Heuristics Miner algorithm”, Eindhoven University of Technology press.

Wil Van Der Aalst, “Service Mining: Using Process Mining to Discover, Check, and Improve Service Behavior”, IEEE Transactions on service computing, vol 6, No.4, OCT-DEC 2013.

] Jochen De Weerdt, Manu De Backer, Jan Vanthienen and Bart Baesens “A Multi-dimensional quality assessment of state-of-the-art process discovery algorithms using real-life event logs”, Elsevier, Nov 18, 2011

Aubrey J Rembert and Clarence Ellis, “An initial approach to mining multiple perspectives of a business process”, TAPIA’09: The fifth Richard Tapia celebration of diversity in computing conference, New York, NY, USA, 2009, ACM.

A Rozinat, R.S. Mans, M.Song and W.M.P van der Aalst, “Discovering simulation models”, Information systems, 34 (3), 305-327, 2009.

Artini M. Lemos et al, “Using process mining in software development process management: A case study”, IEEE, 2011,( ISBN 978-1-4577-0653-0/11)

Wil Van Der Aalst “Process Mining:Discovery, Conformance and Enhancement of Business processes”, Springer, Verlag, Berlin(ISBN 978-3-642-19344-6)

Wil M.P. van der Aalst, Schahram Dustdar, “Process Mining manifesto”, Proc. Business process management workshop, IEEE Task Force on Process Mining. 2011.

Zhengxing Huang, Xudong Lu, and Huilong Duan, “A Task Operation Model for Resource Allocation Optimization in Business Process Management”, IEEE transactions on systems, man, and cybernetics, September 2012.

W. M. P. van der Aalst, A. J. M. M. Weijters,L. Maruster, "Work ow mining: Discovering process models from event logs", IEEE Trans. Knowl. Data Eng.16 (2004) 1128 - 1142.

A. K. Alves de Medeiros, B. F. van Dongen, W. M. P. van der Aalst, A. J. M. M. Weijters, "Process Mining: Extending the alpha-algorithm to Mine Short Loops", BETA Working Paper Series 113, TU Eindhoven, 2004.

A. J. M. M. Weijters, W. M. P. van der Aalst, A. K. Alves de Medeiros, Process Mining with the HeuristicsMiner algorithm, BETAWorking Paper Series 166, TU Eindhoven, 2006.

C. W. Gunther, W. M. P. van der Aalst, "Fuzzy mining - adaptive process simplication based on multiperspective metrics", in: [16], pp. 328-343.

L. Maruster, A. J. M. M. Weijters, W. M. P. van der Aalst, A. van den Bosch, "A rule-based approach for process discovery: Dealing with noise and imbalance in process logs.” Data Mining and Knowledge Discovery 13 (2006), 67-87.

A. K. Alves de Medeiros, A. J. M. M.Weijters, W. M. P.van der Aalst, "Genetic process mining: an experimental evaluation", Data Mining and Knowledge Discovery 14 (2007) 245-304.

G. Alonso, P. Dadam, M. Rosemann (Eds.), Business Process management, 5th International Conference, BPM 2007, Brisbane, Australia, September 24-28, 2007, Proceedings, volume 4714 of Lecture Notes in Computer Science, Springer, 2007.


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