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2018 | OriginalPaper | Chapter

Rule-Mining and Clustering in Business Process Analysis

Authors : Paul N. Taylor, Stephanie Kiss

Published in: Artificial Intelligence XXXV

Publisher: Springer International Publishing

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Abstract

The analysis of complex business processes is a challenging topic. Machine learning provides many tools to help with the analysis/understanding of complex data. In this paper we present the application of two types of technique to this domain. First, rule mining techniques to discover relationships between process behaviour and outcomes. Second, a technique presented is one suitable for clustering arbitrary length directed acyclic graphs such as those that represent business process executions. Both cases are presented in the context of a real business process.

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Metadata
Title
Rule-Mining and Clustering in Business Process Analysis
Authors
Paul N. Taylor
Stephanie Kiss
Copyright Year
2018
Book
Artificial Intelligence XXXV

Print ISBN: 978-3-030-04190-8

Electronic ISBN: 978-3-030-04191-5

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-030-04191-5_22

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