Abstract

Most business processes are today rooted into an informa-tion system recording operational events in log files. Process Mining algorithms exploit this information to discover and qualify differences between observed and modelled process. However, the output of these algorithms are not clearly con-nected with business properties. Our work faces these lim-itations by proposing an approach for calibrating Process Mining results based on the Business Rules adopted by an organisation. The general idea relates on applying Process Mining algorithms on subsequent refinements of the event log, flltering process executions based on Business Rules. This way we are able to associate these results with specific characterisations of the process, as entailed by the corre-sponding Business Rules. This approach is confronted to a real world scenario using data provided by an Italian man-ufacturing company.

Autore Pugliese

• Corallo Angelo , Lazoi Mariangela

Tutti gli autori

• Ceravolo P. , Azzini A. , Damiani E. , Lazoi M. , Marra M. , Corallo A.

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2016

ISSN

Non Disponibile

ISBN

Non Disponibile

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

3

Ultimo Aggiornamento Citazioni

22/04/2018

Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile