Combining Semantic Lifting and Ad-hoc Contextual Analysis in a Data Loss Scenario - Data-Driven Process Discovery and Analysis Access content directly
Conference Papers Year : 2015

Combining Semantic Lifting and Ad-hoc Contextual Analysis in a Data Loss Scenario

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.
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hal-01746409 , version 1 (29-03-2018)

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  • HAL Id : hal-01746409 , version 1

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Antonia Azzini, Ernesto Damiani, Francesco Zavatarelli. Combining Semantic Lifting and Ad-hoc Contextual Analysis in a Data Loss Scenario. 3rd International Symposium on Data-Driven Process Discovery and Analysis (SIMPDA), Aug 2013, Riva del Garda, Italy. pp.87-109. ⟨hal-01746409⟩
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