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Process mining through artificial neural networks and support vector machines: A systematic literature review

Ana Rocío Cárdenas Maita (School of Arts, Sciences and Humanities, University of São Paulo, São Paulo, Brazil)
Lucas Corrêa Martins (School of Arts, Sciences and Humanities, University of São Paulo, São Paulo, Brazil)
Carlos Ramón López Paz (Faculty of Computer Engineering, Higher Polytechnic Institute “José Antonio Echeverría”, Havana, Cuba)
Sarajane Marques Peres (School of Arts, Sciences and Humanities, University of São Paulo, São Paulo, Brazil)
Marcelo Fantinato (School of Arts, Science, and Humanities, University of São Paulo, São Paulo, Brazil)

Business Process Management Journal

ISSN: 1463-7154

Article publication date: 2 November 2015

4033

Abstract

Purpose

Process mining is a research area used to discover, monitor and improve real business processes by extracting knowledge from event logs available in process-aware information systems. The purpose of this paper is to evaluate the application of artificial neural networks (ANNs) and support vector machines (SVMs) in data mining tasks in the process mining context. The goal was to understand how these computational intelligence techniques are currently being applied in process mining.

Design/methodology/approach

The authors conducted a systematic literature review with three research questions formulated to evaluate the use of ANNs and SVMs in process mining.

Findings

The authors identified 11 papers as primary studies according to the criteria established in the review protocol. Most of them deal with process mining enhancement, mainly using ANNs. Regarding the data mining task, the authors identified three types of tasks used: categorical prediction (or classification); numeric prediction, considering the “regression” type, and clustering analysis.

Originality/value

Although there is scientific interest in process mining, little attention has been specifically given to ANNs and SVM. This scenario does not reflect the general context of data mining, where these two techniques are widely used. This low use may be possibly due to a relative lack of knowledge about their potential for this type of problem, which the authors seek to reverse with the completion of this study.

Keywords

Acknowledgements

This work was supported by Fapesp (São Paulo Research Foundation) and Capes (Coordination for the Improvement of Higher Education Personnel), Brazil.

Citation

Maita, A.R.C., Martins, L.C., López Paz, C.R., Peres, S.M. and Fantinato, M. (2015), "Process mining through artificial neural networks and support vector machines: A systematic literature review", Business Process Management Journal, Vol. 21 No. 6, pp. 1391-1415. https://doi.org/10.1108/BPMJ-02-2015-0017

Publisher

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Emerald Group Publishing Limited

Copyright © 2015, Emerald Group Publishing Limited

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