Process mining is a process management technique to extract knowledge from the event logs recorded by an information system. We show how applying an appropriate semantic lifting to the eventand workflow log may help to discover the process that is actually being executed. Moreover, we show how it is possible to extract not only knowledge about the structure of the process, but also to verify if some nonfunctional properties, such as security properties, hold during the process execution.
Using semantic lifting for improving process mining : a data loss prevention system case study / A. Azzini, C. Braghin, E. Damiani, F. Zavatarelli - In: SIMPDA 2013 : data-driven process discovery and analysis : proceedings of the 3rd International symposium on data-driven process discovery and analysis, co-located with 39th International conference on very large databases (VLDB 2013) : Riva del Garda, Italy, august 30, 2013 / [a cura di] R. Accorsi, P. Ceravolo, P. Cudre-Mauroux. - [s.l] : CEUR, 2013 Aug. - pp. 62-73 (( Intervento presentato al 3. convegno International Symposium on Data-driven Process Discovery and Analysis (SIMPDA) tenutosi a Riva del Garda (TN) nel 2013.
Using semantic lifting for improving process mining : a data loss prevention system case study
A. AzziniPrimo
;C. BraghinSecondo
;E. DamianiPenultimo
;F. ZavatarelliUltimo
2013
Abstract
Process mining is a process management technique to extract knowledge from the event logs recorded by an information system. We show how applying an appropriate semantic lifting to the eventand workflow log may help to discover the process that is actually being executed. Moreover, we show how it is possible to extract not only knowledge about the structure of the process, but also to verify if some nonfunctional properties, such as security properties, hold during the process execution.
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