Provided by: Eindhoven University of Technology
Topic: Big Data
Date Added: Oct 2011
Process mining serves a bridge between data mining and business process modeling. The goal is to extract process related knowledge from event data stored in information systems. One of the most challenging process mining tasks is process discovery, i.e., the automatic construction of process models from raw event logs. Today there are dozens of process discovery techniques generating process models using different notations (petri nets, EPCs, BPMN, heuristic nets, etc.). This paper focuses on the representational bias used by these techniques.