TY  - JOUR
A1  - Baier, Thomas
A1  - Di Ciccio, Claudio
A1  - Mendling, Jan
A1  - Weske, Mathias
T1  - Matching events and activities by integrating behavioral aspects and label analysis
JF  - Software and systems modeling
N2  - Nowadays, business processes are increasingly supported by IT services that produce massive amounts of event data during the execution of a process. These event data can be used to analyze the process using process mining techniques to discover the real process, measure conformance to a given process model, or to enhance existing models with performance information. Mapping the produced events to activities of a given process model is essential for conformance checking, annotation and understanding of process mining results. In order to accomplish this mapping with low manual effort, we developed a semi-automatic approach that maps events to activities using insights from behavioral analysis and label analysis. The approach extracts Declare constraints from both the log and the model to build matching constraints to efficiently reduce the number of possible mappings. These mappings are further reduced using techniques from natural language processing, which allow for a matching based on labels and external knowledge sources. The evaluation with synthetic and real-life data demonstrates the effectiveness of the approach and its robustness toward non-conforming execution logs.
KW  - Process mining
KW  - Event mapping
KW  - Business process intelligence
KW  - Constraint satisfaction
KW  - Declare
KW  - Natural language processing
Y1  - 2018
U6  - https://doi.org/10.1007/s10270-017-0603-z
SN  - 1619-1366
SN  - 1619-1374
VL  - 17
IS  - 2
SP  - 573
EP  - 598
PB  - Springer
CY  - Heidelberg
ER  -