A review of business process mining: state‐of‐the‐art and future trends

Abstract

Purpose This paper seeks to examine the area of business process mining, providing an overview of state‐of‐the‐art techniques. An outline of the main problems experienced in the practice of process mining is given along with reference to work that addresses the most challenging issues experienced in this field. This paper also aims to examine the application of soft computing techniques to process‐mining problems. Design/methodology/approach This paper is based on a comprehensive review of literature covering more than 50 research papers. These papers are analysed to identify current trends and future research directions in the field. Findings Process‐mining techniques are now becoming available as graphical interface‐driven software tools, where flow diagram representations of processes may be manipulated as part of the mining task. A significant number of papers employ mining heuristics to aid in the task of process discovery. Soft computing algorithms are increasingly being investigated to aid the accuracy and speed of mining algorithms. Many papers exist that address common mining problems such as noise and mining loops. However, problems such as duplicate tasks, mining perspectives and delta analysis require further research. Originality/value The contribution of this paper is to provide a summary of the current trends in process‐mining practice and point out future research directions. A review of the work in this new and expanding area has been provided in the form of illustrative graphs and tables that identify the trends in this area. This is the most comprehensive and up‐to‐date review of business process‐mining literature.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 180 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.