Using semantic lifting for improving process mining: A data loss prevention system case study

Antonia Azzini, Chiara Braghin, Ernesto Damiani, Francesco Zavatarelli

Research output: Contribution to journalConference articlepeer-review

13 Scopus citations

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 event and workflow log may help to discover the process that is actually being executed. In particular, we show how it is possible to extract not only knowledge about the structure of the process, but also to verify if some non-functional properties, such as security properties, hold during the process execution.

Original languageBritish English
Pages (from-to)62-73
Number of pages12
JournalCEUR Workshop Proceedings
Volume1027
StatePublished - 2013
Event3rd International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2013 - Co-located with 39th International Conference on Very Large Databases, VLDB 2013 - Riva del Garda, Italy
Duration: 30 Aug 201330 Aug 2013

Fingerprint

Dive into the research topics of 'Using semantic lifting for improving process mining: A data loss prevention system case study'. Together they form a unique fingerprint.

Cite this