Combining semantic lifting and ad-hoc contextual analysis in a data loss scenario

Antonia Azzini, Ernesto Damiani, Francesco Zavatarelli

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this work we introduce the knowledge acquisition procedure supported in the KITE.it process management framework. We then illustrate how Process Mining techniques are supported in this framework proposing a running example featured in a Data Loss scenario. We then provide some lesson learned that can be generalized in similar contexts. In particular, we show how applying an appropriate Semantic Lifting to the log may help to discover behavioral patterns of the process that is actually being executed. Our conclusions spotlight that it is viable to verify whether some non-functional properties hold during the process execution. Moreover, we describe the impact that Semantics Lifting has on support and confidence of the inferred probabilities of observing these behavioral patterns.

Original languageBritish English
Title of host publicationData-Driven Process Discovery and Analysis - 3rd IFIP WG 2.6, 2.12 International Symposium, SIMPDA 2013, Revised Selected Papers
EditorsRafael Accorsi, Philippe Cudre-Mauroux, Paolo Ceravolo
PublisherSpringer Verlag
Pages87-109
Number of pages23
ISBN (Electronic)9783662464359
DOIs
StatePublished - 2015
Event3rd IFIP WG 2.6, 2.12 International Symposium on Data-driven Process Discovery and Analysis, SIMPDA 2013 - Riva del Garda, Italy
Duration: 30 Aug 201330 Aug 2013

Publication series

NameLecture Notes in Business Information Processing
Volume203
ISSN (Print)1865-1348

Conference

Conference3rd IFIP WG 2.6, 2.12 International Symposium on Data-driven Process Discovery and Analysis, SIMPDA 2013
Country/TerritoryItaly
CityRiva del Garda
Period30/08/1330/08/13

Keywords

  • Business process monitoring
  • Knowledge acquisition process
  • Semantic lifting

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