PreDiCtS : a personalised service discovery and composition framework

Abstract

The proliferation of Web Services is fostering the need for applications to provide more personalisation during the service discovery and composition phases. An application has to cater for different types of users and seamlessly provide suitably understandable and refined replies. In this paper, we describe the motivating details behind PreDiCtS1, a framework for personalised service discovery and composition. The underlying concept behind PreDiCtS is that, similar service composition problems could be tackled in a similar manner by reusing past composition best practices. These have to be useful and at the same time flexible enough to allow for adaptations to new problems. For this reason we are opting to use template-based composition information. PreDiCtS’s retrieval and refinement technique is based on conversational case-based reasoning (CCBR) and makes use of a core OWL ontology called CCBROnto for case representations.