A Survey on Conformance Checking of Event Logs and Process Models in Business Organization
DOI:
https://doi.org/10.61841/5mpyah32Keywords:
Process Mining (PM), Conformance Checking, Process Decomposition, Event Logs, Process Model, Business Process Management (BPM)Abstract
Process mining is a developing technology. It is used in the field of administration. It deals with Process Discovery (PD), Conformance Checking (CC), and Process Enhancement (PE) based on logs and models. In conformance checking (CC), it takes the current process model as input and compares it with the event logs of the actual execution of the business process and the resulting model by capturing the predictable performance of the given process. CC can be used to check whether the process model as recorded in the event log conforms to the process model and vice versa. It is challenging to determine the optimal alignment for each of the event logs and the process model because of their similarity with the event log. The main objective of this study is to provide an overall knowledge about the CC in context with the event logs and process model. A series of metrics based on prior work are introduced to perform conformance checking. The proposed metrics include fitness, precision, generalization, and simplicity.
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[1] Wei Song, Xiaoxu Xia, Hans-Arno Jacobsen, Pengcheng Zhang, and Hao Hu, “Efficient Alignment between Event Logs and Process Models," IEEE Transactions on Services Computing, Vol. 10, January/February 2017.
[2] Jianmin Wang, Raymond K. Wong, Jianwei Ding, Qinlong Guo, and Lijie Wen, “Efficient Selection of Process Mining Algorithms," IEEE Transactions on Services Computing, October 2013.
[3] Jan Claes and Geert Poels, “Merging Event Logs for Process Mining: A Rule-Based Merging Method and Rule Suggestion Algorithm," Expert Systems with Applications, Elsevier, June 2014.
[4] Jianmin Wang, Shaoxu Song, Xiaochen Zhu, and Xuemin Lin, “Efficient Recovery of Missing Events," IEEE Transactions on Knowledge and Data Engineering, Vol. 28, No. 11, Nov. 2016.
[5] Wei Song, Xiaoxu Xia, Hans-Arno Jacobsen, Pengcheng Zhang, and Hao Hu, “Heuristic Recovery of Missing Events in Process Logs," IEEE International Conference on Web Services, pp. 105-112, 2015.
[6] TitasSavickas and OlegasVasilecas, “Business Process Event Log Use for Activity Sequence
Analysis”, IEEE Conference Publications, pp: 1 - 4, 2015.
[7] Weekit Chomyat and Wichain Premchaiswadi, “Process Mining on Medical Treatment History Using Conformance Checking," International Conference on ICT and Knowledge Engineering, pp. 77-83, 2016.
[8] Stefan Schonig, Claudio Di Ciccio, Fabrizio M. Maggi, and Jan Mendling, “Discovery of MultiPerspective Declarative Process Models," https://www.researchgate.net/publication/308337823, DOI:10.1007/978-3-319-46295-0_6, October 2016.
[9] IvonaZakarija, FranoSkopljanac-Maina and Bruno Blaskovic, “Discovering Process Model from Incomplete Log using Process Mining”, International Symposium of Electronics in Marine ELMAR,Vol.28-30, Sep 2015.
[10] Esmita Gupta “Process Mining Algorithms” International Journal of Advance Research In Science and Engineering, Vol. No.3, Issue No.11, Nov. 2014.
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