An End-to-End Configuration-Based Framework for Automatic SWS Composition

Semantic Web Service (SWS) composition is a challenging AI problem. We describe a theoretical and experimental framework based upon finite model search for constrained object models to address this problem. In many AI situations the input is rather simple, and the results complex to obtain. SWS composition requests themselves can turn very complex, and the problem of building these requests can be viewed as an AI problem of its own. This paper presents an operational end to end approach to composing/publishing Semantic Web Services involving two main reasoning stages. Composing is first performed at the abstract level of goals (each roughly representing a discovery request), which yields a composition request at the workflow level. The resulting workflow is finally processed to generate a valid publishable semantic web service. We present experimental results obtained on industrial use cases during the DIP project.