Abstract
Industrial, scientific, and commercial applications use information systems to trace the execution of a business process. Relevant events are registered in massive logs and process mining techniques are used to automatically discover knowledge that reveals the execution and organization of the process instances (cases). In this paper, we investigate the use of a multi-level relational frequent pattern discovery method as a means of process mining. In order to process such massive logs we resort to a Grid-based implementation of the knowledge discovery algorithm that distributes the computation on several nodes of a Grid platform. Experiments are performed on real event logs. © 2008 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Turi, A., Appice, A., Ceci, M., & Malerba, D. (2008). A grid-based multi-relational approach to process mining. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5181 LNCS, pp. 701–709). https://doi.org/10.1007/978-3-540-85654-2_61
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
