We present a novel approach and a system for automated selection of building blocks, by exploiting business processes semantics. The selection process is based on a novel greedy concept covering algorithm, which computes, given a description of the request, the set of needed building blocks. If such a set does not exist the algorithm returns the covered subset and explanation information on both the left-uncovered part and conflicting part of the request description, exploiting non-standard inference services. The requested description can be expressed as conjunction of mandatory requirements and preferences. In order to efficiently cope with large datasets a further enhancement is proposed, exploiting pre-classification techniques using a Description Logics reasoning engine in conjunction with a RDBMS to reduce the computational burden. The approach has been deployed in a system specifically designed for SAP R/3 best practices reusability, which is fully functional and is currently being evaluated in an industrial setting
Automated Building Blocks Selection based on Business Processes Semantics in ERPs / DI NOIA, Tommaso; DI SCIASCIO, Eugenio; Donini, F. M.; Tinelli, E.; Di Cugno, F.; Ragone, A.. - In: SERVICE ORIENTED COMPUTING AND APPLICATIONS. - ISSN 1863-2386. - 1:3(2007), pp. 171-184. [10.1007/s11761-007-0014-z]
Automated Building Blocks Selection based on Business Processes Semantics in ERPs
DI NOIA, Tommaso;DI SCIASCIO, Eugenio;
2007-01-01
Abstract
We present a novel approach and a system for automated selection of building blocks, by exploiting business processes semantics. The selection process is based on a novel greedy concept covering algorithm, which computes, given a description of the request, the set of needed building blocks. If such a set does not exist the algorithm returns the covered subset and explanation information on both the left-uncovered part and conflicting part of the request description, exploiting non-standard inference services. The requested description can be expressed as conjunction of mandatory requirements and preferences. In order to efficiently cope with large datasets a further enhancement is proposed, exploiting pre-classification techniques using a Description Logics reasoning engine in conjunction with a RDBMS to reduce the computational burden. The approach has been deployed in a system specifically designed for SAP R/3 best practices reusability, which is fully functional and is currently being evaluated in an industrial settingI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.