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

Author:

Tiwari A.,Turner C.J.,Majeed B.

Abstract

PurposeThis 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/approachThis 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.FindingsProcess‐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/valueThe 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.

Publisher

Emerald

Subject

Business, Management and Accounting (miscellaneous),Business and International Management

Cited by 91 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Parallel Flexible Heuristic Miner for Process Discovery;SN Computer Science;2023-07-10

2. An Experimental Outlook on Quality Metrics for Process Modelling: A Systematic Review and Meta Analysis;Algorithms;2023-06-10

3. Quantifying the reliability of defects located by bridge inspectors through human observation behavioral analysis;Developments in the Built Environment;2023-04

4. Using process mining for workarounds analysis in context: Learning from a small and medium-sized company case;International Journal of Information Management Data Insights;2023-04

5. Process mining to discover online learning behaviour;2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM);2023-01-03

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3