Semantic Matching of Web Services Capabilities
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
A software framework for matchmaking based on semantic web technology
WWW '03 Proceedings of the 12th international conference on World Wide Web
ICWS '04 Proceedings of the IEEE International Conference on Web Services
Flexible and Efficient Matchmaking and Ranking in Service Directories
ICWS '05 Proceedings of the IEEE International Conference on Web Services
Automated semantic web service discovery with OWLS-MX
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Discovering Semantic Web Services with and without a Common Ontology Commitment
SCW '06 Proceedings of the IEEE Services Computing Workshops
WSMO-MX: A Logic Programming Based Hybrid Service Matchmaker
ECOWS '06 Proceedings of the European Conference on Web Services
Optimizing web search using social annotations
Proceedings of the 16th international conference on World Wide Web
Preference-based selection of highly configurable web services
Proceedings of the 16th international conference on World Wide Web
Similarity search for web services
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Introduction to Information Retrieval
Introduction to Information Retrieval
Ranking in folksonomy systems: can context help?
Proceedings of the 17th ACM conference on Information and knowledge management
Efficient Semantic Web Service Discovery in Centralized and P2P Environments
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
Top-k dominant web services under multi-criteria matching
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Information retrieval in folksonomies: search and ranking
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
An efficient algorithm for OWL-S based semantic search in UDDI
SWSWPC'04 Proceedings of the First international conference on Semantic Web Services and Web Process Composition
Enabling trust-aware semantic web service selection a flexible and personalized approach
Proceedings of the 12th International Conference on Information Integration and Web-based Applications & Services
Towards a quality service layer for web 2.0
WISS'10 Proceedings of the 2010 international conference on Web information systems engineering
Towards scalability of reputation and QoS based web services discovery using agents and ontologies
Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services
An ontology-based mechanism for automatic categorization of web services
Concurrency and Computation: Practice & Experience
WSTRank: ranking tags to facilitate web service mining
ICSOC'12 Proceedings of the 10th international conference on Service-Oriented Computing
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State-of-the-art discovery of Semantic Web services is based on hybrid algorithms that combine semantic and syntactic matchmaking. These approaches are purely based on similarity measures between parameters of a service request and available service descriptions, which, however, fail to completely capture the actual functionality of the service or the quality of the results returned by it. On the other hand, with the advent of Web 2.0, active user participation and collaboration has become an increasingly popular trend. Users often rate or group relevant items, thus providing valuable information that can be taken into account to further improve the accuracy of search results. In this paper, we tackle this issue, by proposing a method that combines multiple matching criteria with user feedback to further improve the results of the matchmaker. We extend a previously proposed dominance-based approach for service discovery, and describe how user feedback is incorporated in the matchmaking process. We evaluate the performance of our approach using a publicly available collection of OWL-S services.