Downloads
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Figure 1
slides/ex1_logdialog.jpg
Viewing the log dialog of exercise1.xes in ProM
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Figure 2
slides/ex1_log_inspect.jpg
Inspecting exercise1.xes in ProM
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Figure 3
slides/ex1_logsummary.jpg
Viewing the log summary of exercise1.xes in ProM
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Figure 4
slides/ex1_inspect_explore.jpg
Using the explorer to inspect the traces in exercise1.xes
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Figure 5
slides/ex1_transSysMiner_Start.jpg
Start the Transition System Miner on exercise1.xes
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Figure 6
slides/ex1_transSysMiner_CorrectSettings.jpg
The correct settings for the Transition System Miner
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Figure 7
slides/ex1_transSysMiner_Result.jpg
The expected resulting transition system
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Figure 8
slides/ex1_petriNet.jpg
The Petri net created from the transition system for exercise1.xes
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Figure 9
slides/ex2_logdialog.jpg
Viewing the log dialog of exercise2.xes in ProM
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Figure 10
slides/ex2_log_inspect.jpg
Inspecting exercise2.xes in ProM
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Figure 11
slides/ex2_inspect_explore.jpg
Using the explorer to inspect the traces in exercise2.xes
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Figure 12
slides/ex2_logsummary.jpg
Viewing the log summary of exercise2.xes in ProM
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Figure 13
slides/ex2_transSysMiner_Result.jpg
The expected resulting transition system
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Figure 14
slides/ex2_petriNet.jpg
The Petri net created from the transition system for exercise2.xes
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Figure 15
slides/ex4_transSys_listResult.jpg
The result of the Transition System Miner on exercise4.xes
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Figure 16
slides/ex4_transSys_PNResult.jpg
The result of the Transition System Miner to Petri net conversion
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Figure 17
slides/ex4_alpha_result.jpg
Result of the alpha-algorithm on exercise4.xes
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Figure 18
slides/ex4_ilp_result.jpg
Result of the ILP Miner on exercise4.xes
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Figure 19
slides/ex4_heuristic_result.jpg
Initial result of the Heuristics Miner
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Figure 20
slides/ex4_heuristic_option_splitJoinSemantics.jpg
Option to visualize the Heuristics net with the split/join semantics
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Figure 21
slides/ex4_heuristic_splitJoinSemantics.jpg
The same Heuristics net but now with split and join semantics shown
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Figure 22
slides/ex4_genetic_default_result.jpg
The result of the Genetic Miner on exercise4.xes
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Figure 23
slides/ex4_genetic_better_result.jpg
The result of the Genetic Miner on exercise4.xes with 200 iterations
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Figure 24
slides/ex5_alpha_result.jpg
Result of the alpha-algorithm on exercise5.xes
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Figure 25
slides/ex5_fuzzy_result.jpg
Result of the Fuzzy Miner on exercise5.xes
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Figure 26
slides/ex5_dottedChart_default_result.jpg
Result of the Dotted Chart on exercise5.xes
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Figure 27
slides/ex5_dottedChart_relativeTime.jpg
Dotted chart with relative time, sorted by case duration
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Figure 28
slides/ex5_dottedChart_organizational.jpg
Dotted chart set to show users and their activities over time
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Figure 29
slides/ex6_ILPMiner_result.jpg
ILP Miner result on exercise6.xes
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Figure 30
slides/ex6_Fuzzy_result.jpg
Fuzzy Miner result on exercise6.xes
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Figure 31
slides/ex6_Fuzzy_MoreEdges.jpg
Fuzzy Miner result on exercise6.xes with Edge cutoff set to 1,000
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Figure 32
slides/ex6_transSysMinerAnalsysis_firstState.jpg
Transition System Analysis result with the first state selected
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Figure 33
slides/ex6_transSysMinerAnalsysis_sojournState4.jpg
Transition System Analysis result with state 4 selected
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Figure 34
slides/ex6_transSysMinerAnalsysis_elapsedLastState.jpg
Transition System Analysis result by elapsed time with the second-last state selected
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Figure 35
slides/ex6_transSysMinerAnalsysis_remainingState8.jpg
Transition System Analysis result by remaining time with state 8 selected
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ProM 6.1
Processes are an integral part of today's world, driving services and internal functionalities in businesses, governmental bodies, and organizations around the globe. While there are plenty of systems available for supporting the execution of such processes, the current practices for monitoring and analyzing this execution in the organizational reality still leaves a lot to be desired. Process Mining is able to fill that gap, providing revolutionary means for the analysis and monitoring of real-life processes.
Process Mining research is concerned with the extraction of knowledge about a (business) process from its process execution logs. Process Mining strives to gain insight into various perspectives, such as the process (or control flow) perspective, the performance, data, and organizational perspective (The processmining.org web site has more in-depth information and scientific publications available).
ProM is an extensible framework that supports a wide variety of process mining techniques in the form of plug-ins.
It is platform independent as it is implemented in Java, and can be downloaded free of charge.
We welcome and support practical applications of ProM, and
we invite researchers and developers to contribute in the form of new plug-ins.
ProM 6.1 is distributed in parts, which offers maximal flexibility.
First, the ProM 6.1 core is distributed as a downloadable package using the GNU Public License (GPL) open source license.
This means that you can download and install ProM 6.1 without restrictions, but that any software that uses the core also needs to be distributed using the GPL license.
Second, the ProM 6.1 plug-ins are distributed as separate packages, which typically use the Lesser GNU Public License (L-GPL) open source license.
Note that the use of third part software might require a plug-in to be issued under a different license than the L-GPL license, but in principle ProM 6.1 plug-ins will use the L-GPL license.
This means that you can download and install the plug-ins without restrictions, and that you are free to distribute software that uses these plug-ins using your own license.
However, if you distribute a changed versions of such a plug-in, you are required to distribute this changed plug-in under the L-GPL license as well.
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Currently, there are already more than 170 plug-ins available, and we support the import of (and the conversion between) several process modeling languages, such as:
There are mining plug-ins, such as:
- Plug-ins supporting control-flow mining techniques (such as the Alpha algorithm and Genetic mining)
- Plug-ins analyzing the organizational perspective (such as the Social Network miner)
- Plug-ins for mining less-structured, flexible processes (such as the Fuzzy Miner)
- (and many more)
Furthermore, there are analysis plug-ins dealing with:
- The verification of process models (e.g., Woflan analysis)
- Verification of Linear Temporal Logic (LTL) formulas on a log
- Performance analysis (Basic statistical analysis, and Performance Analysis with a given process model)
- (and many more)
Finally, ProM sports a number of log filters, which are a valuable tool for cleaning logs from undesired, or unimportant, artefacts.
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