Clustering-Based Semantic Web Service Matchmaking with Automated Knowledge Acquisition
WISM '09 Proceedings of the International Conference on Web Information Systems and Mining
Optimizing queries to remote resources
Journal of Intelligent Information Systems
Scalable and Distributed Processing of Scientific XML Data
GRID '11 Proceedings of the 2011 IEEE/ACM 12th International Conference on Grid Computing
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There is a critical need to design and develop tools that abstract away the fundamental complexity of XML-based Web services specifications and toolkits, and provide an elegant, intuitive, simple, and powerful query-based invocation system to end users. Web services based tools and standards have been designed to facilitate seamless integration and development for application developers. As a result, current implementations require the end user to have intimate knowledge of Web services and related toolkits, and users often play an informed role in the overall Web services execution process. We employ a self-learning mechanism and a set of algorithms and optimizations to match user queries with corresponding operations in Web services. Our system uses Semantic Web concepts and Ontologies in the process of automating Web services matchmaking. We present performance analysis of our system and quantify the exact gains in precision and recall due to the knowledge acquisition algorithms.