On the Selection of Process Mining Tools

被引：12

作者：

Drakoulogkonas, Panagiotis ^{[1
]}

Apostolou, Dimitris ^{[1
]}

机构：

[1] Univ Piraeus, Sch Informat & Commun Technol, Dept Informat, 80 M Karaoli & A Dimitriou St, Piraeus 18534, Greece

来源：

ELECTRONICS | 2021年 / 10卷 / 04期

关键词：

process mining; software tools; comparative analysis methodology; comparison criteria; ontology; decision tree; analytic hierarchy process (AHP); PERFORMANCE;

D O I：

10.3390/electronics10040451

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Process mining is a research discipline that applies data analysis and computational intelligence techniques to extract knowledge from event logs of information systems. It aims to provide new means to discover, monitor, and improve processes. Process mining has gained particular attention over recent years and new process mining software tools, both academic and commercial, have been developed. This paper provides a survey of process mining software tools. It identifies and describes criteria that can be useful for comparing the tools. Furthermore, it introduces a multi-criteria methodology that can be used for the comparative analysis of process mining software tools. The methodology is based on three methods, namely ontology, decision tree, and Analytic Hierarchy Process (AHP), that can be used to help users decide which software tool best suits their needs.

引用

页码：1 / 24

页数：23

共 35 条

[1]

Agarwal N., 2014, ADV COMPUT SCI INF T, V1, P26

[2] Measuring the Impact of Accurate Feature Selection on the Performance of RBM in Comparison to State of the Art Machine Learning Algorithms [J].

Aldwairi, Tamer ;

Perera, Dilina ;

Novotny, Mark A. .

ELECTRONICS, 2020, 9 (07) :1-13

[3]

[Anonymous], 2009, COMMUN ACM

[4]

[Anonymous], 2015, ATAED PETR NETS ACSD

[5]

[Anonymous], 2004, A Practical Guide To Building OWL Ontologies Using Protege 4 and CO-ODE Tools

[6] Automated Discovery of Process Models from Event Logs: Review and Benchmark [J].

Augusto, Adriano ;

Conforti, Raffaele ;

Dumas, Marlon ;

La Rosa, Marcello ;

Maggi, Fabrizio Maria ;

Marrella, Andrea ;

Mecella, Massimo ;

Soo, Allar .

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2019, 31 (04) :686-705

[7]

Celi K., 2018, AJIT-e Online Academic Journal of Information Technology, V9, P97, DOI DOI 10.5824/1309-1581.2018.4.007.X

[8]

Claes J, 2013, LECT NOTES BUS INF P, V132, P187

[9]

Da Silva L.F.N., 2014, Process Mining: Application to a Case Study

[10]

Dakic D., 2019, P 2019 IEEE 17 INT S

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