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In addition, the extraction process (mining and chemical treatment) poses environmental challenges, especially in regions where it occurs.
To tackle this challenge, we propose a process mining [27] method based on transfer learning [28].
Assessing the quality of discovered process models is an essential element, both for conducting process mining research as well as for the use of process mining in practice.
Celonis describes what its software does as a new sub-set category of big-data mining, called process mining.
It launched in 2011 in Munich with this idea of helping companies understand their processes, which they call process mining.
In this paper, we propose process mining techniques and tools to analyze ad-hoc processes.
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Table 2 presents the data elements considered important by each of these studies, compares them with the ones needed for our own process-mining studies [ 29], and presents an overall importance rate based on the frequency each element is referred.
The technique to build a process corresponding to an event log is called Process Mining [5].
This automated documentation, if based on transaction and master data from the IT systems connected to the logistic process, is called Process Mining.
Our research investigates how to apply context awareness based on Machine Learning in Process Mining for logistic processes and demonstrates its performance in a logistic scenario.
Adding context awareness to unstructured event data in logistics has the potential to improve the results of Process Mining.
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process exploitation
production mining
process industry
process sector
process ore
organization mining
process insurance
process metallurgy
process extraction
treat mining
process production
process removal
treatment mining
operation mining
process person
process analysis
process improvement
process management
process shot
process process
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