Mining social tags to predict mashup patterns
SMUC '10 Proceedings of the 2nd international workshop on Search and mining user-generated contents
Trade-off between complexity of structured tagging and effectiveness of web service retrieval
ICWE'10 Proceedings of the 10th international conference on Current trends in web engineering
Backing composite web services using formal concept analysis
ICFCA'11 Proceedings of the 9th international conference on Formal concept analysis
User-Driven automatic resource retrieval based on natural language request
NLDB'12 Proceedings of the 17th international conference on Applications of Natural Language Processing and Information Systems
Socially-Enriched semantic mashup of web APIs
ICSOC'12 Proceedings of the 10th international conference on Service-Oriented Computing
WSTRank: ranking tags to facilitate web service mining
ICSOC'12 Proceedings of the 10th international conference on Service-Oriented Computing
A system for web widget discovery using semantic distance between user intent and social tags
SocInfo'12 Proceedings of the 4th international conference on Social Informatics
Fully automated resource retrieval in telecommunications and internet converged environments
Information Systems Frontiers
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In this paper, we propose a novel way of modeling web services using folksonomies. The key advantage of our model is that it allows a large number of users to participate, easily, in annotating services with tags. This is in contrast to more expressive, logic based models of services, such as Semantic Web Service models, which require significant expertise for annotation and maintenance. Our folksonomy-based model allows associating semantic constraints on the input and output messages of web service operations using tags obtained from a folksonomy. We show how the model can be used for discovery and composition of services. We also describe a planner that uses this model to compose services and create workflows, automatically. We present performance results for the planner and our experiences in using this model in a sample real-world domain.