Getting into Information Retrieval
ESSIR '00 Proceedings of the Third European Summer-School on Lectures on Information Retrieval-Revised Lectures
QoS-Aware Middleware for Web Services Composition
IEEE Transactions on Software Engineering
Preference-based selection of highly configurable web services
Proceedings of the 16th international conference on World Wide Web
A framework for QoS-based Web service contracting
ACM Transactions on the Web (TWEB)
Discovering Semantic Web services using SPARQL and intelligent agents
Web Semantics: Science, Services and Agents on the World Wide Web
A qos-aware selection model for semantic web services
ICSOC'06 Proceedings of the 4th international conference on Service-Oriented Computing
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Automating service selection using semantic approaches have been extensively studied in recent years. In fact, given the big number of provider offers, sourcing of the most relevant service to the client intentions is a complex task especially when providers and customers don't share the same knowledge degree. In particular, differentiating between very similar offers satisfying the same number of client constraints is still a challenging task. In this paper, we present a novel semantic scoring approach that helps clients to select the most appropriate service offer according to their intentions. Our approach detects direct and indirect semantic correspondences between these intentions and the available offers using ontological models. It fairly evaluates these offers and ranks them according to their semantic closeness to the client intentions taking into account both functional and QoS properties. Our ranking is based on a deep examination of provider offers and can distinguish between services that look the same for non expert clients.