Abstract
The issue of devising efficient and effective solutions for supporting the analysis of process logs has recently received great attention from the research community, as effectively accomplishing any business process management task requires understanding the behavior of the processes. In this paper, we propose a new framework supporting the analysis of process logs, exhibiting two main features: a flexible data model (enabling an exhaustive representation of the facets of the business processes that are typically of interest for the analysis) and a graphical query language, providing a user-friendly tool for easily expressing both selection and aggregate queries over the business processes and the activities they are composed of. The framework can be easily and efficiently implemented by leveraging either “traditional” relational DBMSs or “innovative” NoSQL DBMSs, such as Neo4J.
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Fazzinga, B., Flesca, S., Furfaro, F., Masciari, E., Pontieri, L., Pulice, C. (2015). A Framework Supporting the Analysis of Process Logs Stored in Either Relational or NoSQL DBMSs. In: Esposito, F., Pivert, O., Hacid, MS., Rás, Z., Ferilli, S. (eds) Foundations of Intelligent Systems. ISMIS 2015. Lecture Notes in Computer Science(), vol 9384. Springer, Cham. https://doi.org/10.1007/978-3-319-25252-0_6
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DOI: https://doi.org/10.1007/978-3-319-25252-0_6
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