Abstract
In this paper, we present a scalable data analysis technique to support efficient event correlation for mining business processes. We propose a two-stages approach to compute correlation conditions and their entailed process instances from event logs using MapReduce framework. The experimental results show that the algorithm scales well to large datasets.
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Reguieg, H., Toumani, F., Motahari-Nezhad, H.R., Benatallah, B. (2012). Using Mapreduce to Scale Events Correlation Discovery for Business Processes Mining. In: Barros, A., Gal, A., Kindler, E. (eds) Business Process Management. BPM 2012. Lecture Notes in Computer Science, vol 7481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32885-5_22
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DOI: https://doi.org/10.1007/978-3-642-32885-5_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32884-8
Online ISBN: 978-3-642-32885-5
eBook Packages: Computer ScienceComputer Science (R0)