DPMine graphical language for automation of experiments in process mining

Process mining is a new direction in the field of modeling and analysis of processes, where the use of information from event logs describing the history of the system behavior plays an important role. Methods and approaches used in the process mining are often based on various heuristics, and experiments with large event logs are crucial for the study and comparison of the developed methods and algorithms. Such experiments are very time consuming, so automation of experiments is an important task in the field of process mining. This paper presents the language DPMine developed specifically to describe and carry out experiments on the discovery and analysis of process models. The basic concepts of the DPMine language as well as principles and mechanisms of its extension are described. Ways of integration of the DPMine language as dynamically loaded components into the VTMine modeling tool are considered. An illustrating example of an experiment for building a fuzzy model of the process discovered from the log data stored in a normalized database is given.