A Divide and Conquer approach for Process Discovery
Publish place: National Conference of Technology, Energy & Data on Electrical & Computer Engineering
Publish Year: 1394
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
TEDECE01_120
تاریخ نمایه سازی: 30 آبان 1394
Abstract:
Extremely rapid growth of event data in many industries –including internet, social networks, cloud computing, are experienced. Process mining techniques aim to extract information from these event logs. However, overwhelming amounts of event data also provide new challenges that often existing process mining techniques cannot deal with. One of the important challenges in process mining is to discover a process model describing observed behavior in the best possible manner. This paper will focus on process discovery in the large . We suggest using a formal composition framework for process discovery. Trough this composition technique, two or more fine-grain process models can be integrated into a value-added coarse-grain process model. This composition reduces processing time of discovery procedure. We prove this algorithm to be able to discover a model of the whole system through a case study
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Authors
Fateme Jafarinejad
AI & Distributed Systems Laboratory, School of Computer Engineering, Shahrood university of Technology Shahrood, Iran
Ali A. Pouyan
AI & Distributed Systems Laboratory, School of Computer Engineering, Shahrood university of Technology Shahrood, Iran
Morteza Zahedi
Web Mining & Pattern Recognition Laboratory, School of Computer Engineering,Shahrood university of Technology Shahrood, Iran
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