Approaching process mining with sequence clustering: Experiments and findings

105Citations
Citations of this article
176Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Sequence clustering is a technique of bioinformatics that is used to discover the properties of sequences by grouping them into clusters and assigning each sequence to one of those clusters. In business process mining, the goal is also to extract sequence behaviour from an event log but the problem is often simplified by assuming that each event is already known to belong to a given process and process instance. In this paper, we describe two experiments where this information is not available. One is based on a real-world case study of observing a software development team for three weeks. The other is based on simulation and shows that it is possible to recover the original behaviour in a fully automated way. In both experiments, sequence clustering plays a central role. © Springer-Verlag Berlin Heidelberg 2007.

Cite

CITATION STYLE

APA

Ferreira, D., Zacarias, M., Malheiros, M., & Ferreira, P. (2007). Approaching process mining with sequence clustering: Experiments and findings. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4714 LNCS, pp. 360–374). Springer Verlag. https://doi.org/10.1007/978-3-540-75183-0_26

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free