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Inducing Declarative Logic-Based Models from Labeled Traces
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Inducing Declarative Logic-Based Models from Labeled Traces
Evelina Lamma1  , Paola Mello2 , Marco Montali2 , Fabrizio Riguzzi1 and Sergio Storari1
| (1) |
ENDIF – Università di Ferrara, Via Saragat, 1 – 44100 – Ferrara, Italy |
| (2) |
DEIS – Università di Bologna, viale Risorgimento, 2 – 40136 – Bologna, Italy |
Abstract
In this work we propose an approach for the automatic discovery of logic-based models starting from a set of process execution
traces. The approach is based on a modified Inductive Logic Programming algorithm, capable of learning a set of declarative
rules.
The advantage of using a declarative description is twofold. First, the process is represented in an intuitive and easily
readable way; second, a family of proof procedures associated to the chosen language can be used to support the monitoring
and management of processes (conformance testing, properties verification and interoperability checking, in particular).
The approach consists in first learning integrity constraints expressed as logical formulas and then translating them into
a declarative graphical language named DecSerFlow.
We demonstrate the viability of the approach by applying it to a real dataset from a health case process and to an artificial
dataset from an e-commerce protocol.
Topics Process mining - Process verification and validation - Logic Programming - DecSerFlow - Careflow
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