A model for web services discovery with QoS
ACM SIGecom Exchanges
QoS-Aware Middleware for Web Services Composition
IEEE Transactions on Software Engineering
A DAML-Based Repository for QoS-Aware Semantic Web Service Selection
ICWS '04 Proceedings of the IEEE International Conference on Web Services
DAML-QoS Ontology for Web Services
ICWS '04 Proceedings of the IEEE International Conference on Web Services
QoS computation and policing in dynamic web service selection
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
A Framework and Ontology for Dynamic Web Services Selection
IEEE Internet Computing
QoSOnt: a QoS Ontology for Service-Centric Systems
EUROMICRO '05 Proceedings of the 31st EUROMICRO Conference on Software Engineering and Advanced Applications
A framework for semantic web services discovery
Proceedings of the 7th annual ACM international workshop on Web information and data management
ECOWS '06 Proceedings of the European Conference on Web Services
An Hybrid, QoS-Aware Discovery of Semantic Web Services Using Constraint Programming
ICSOC '07 Proceedings of the 5th international conference on Service-Oriented Computing
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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Discovery tasks in the context of Semantic Web Services are generally performed using Description Logics. However, this formalism is not suited when non-functional, numerical parameters are involved in the discovery process. Furthermore, in selection tasks, where an optimization algorithm is needed, DLs are not capable of computing the optimum. Although there are DLs extensions that can handle numerical parameters, they bring decidability problems. Other solutions, as hybrid approaches which use DLs in functional discovery and other formalisms in non-functional selection, do not provide a semantic framework to describe user preferences based on non-functional properties. In this work, we propose to semantically describe user preferences, so they can be used to perform selection within a hybrid solution. By using semantically described utility functions in order to define user preferences, our proposal enables interoperability between service offers and demands, while providing a high level of expressiveness in these preferences and including them within SWS descriptions.