An Experimental Evaluation of Passage-Based Process Discovery

In the area of process mining, the ILP miner is known for the fact that it always returns a petri net that perfectly fits a given event log. Like for most process discovery algorithms, its complexity is linear in the size of the event log and exponential in the number of event classes (i.e., distinct activities). As a result, the potential gain by partitioning the event classes is much higher than the potential gain by partitioning the traces in the event logs over multiple event logs.

Provided by: Technische Universitat Munchen Topic: Big Data Date Added: Jul 2012 Format: PDF

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