Process Mining a Comparative Study

Abstract: The systems that support today‟s globally distributed and agile businesses are steadily growing in size and generating numerous events. Business Intelligence aims to support and improve decision making processes by providing methods and tools for analyzing the data. Process mining builds the bridge between Data Mining as a Business Intelligence approach and Business Process Management. Its primary objective is the discovery of process models based on available event log data.
Many process mining algorithms have been proposed recently, there does not exist a widely-accepted benchmark to evaluate and compare these process mining algorithms. As a result, it can be difficult to choose a suitable process mining algorithm for a given enterprise or application domain.
This paper proposes a solution to evaluate and compare these process mining algorithms efficiently, so that businesses can efficiently select the process mining algorithms that are most suitable for a given model set.

Keywords: Process mining, Heuristic miner, Genetic miner, Fuzzy miner