Name
Abstract | ||
|---|---|---|
In this work we propose an approach for the automatic discoveryof logic-based models starting from a set of process executiontraces. The approach is based on a modified Inductive Logic Programmingalgorithm, capable of learning a set of declarative rules. The advantage of using a declarative description is twofold. First, theprocess is represented in an intuitive and easily readable way; second,a family of proof procedures associated to the chosen language can beused to support the monitoring and management of processes (conformancetesting, properties verification and interoperability checking, inparticular). The approach consists in first learning integrity constraints expressedas logical formulas and then translating them into a declarative graphicallanguage named DecSerFlow. We demonstrate the viability of the approach by applying it to a realdataset from a health case process and to an artificial dataset from ane-commerce protocol. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-75183-0_25 | BPM |
Keywords | Field | DocType |
declarative logic-based model,artificial dataset,process executiontraces,ane-commerce protocol,declarative graphicallanguage,declarative description,learning integrity constraint,chosen language,declarative rule,automatic discoveryof logic-based model,health case process | Programming language,Computer science,Interoperability,Inductive logic,Theoretical computer science,Data integrity,Logic programming,Process mining,Distributed computing | Conference |
Volume | ISSN | ISBN |
4714 | 0302-9743 | 3-540-75182-3 |
Citations | PageRank | References |
34 | 1.33 | 14 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Evelina Lamma | 1 | 1268 | 109.21 |
| Paola Mello | 2 | 444 | 21.33 |
| Marco Montali | 3 | 1280 | 99.36 |
| Fabrizio Riguzzi | 4 | 799 | 67.94 |
| Sergio Storari | 5 | 300 | 18.30 |