There is a critical need to design

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If the model of free-form queries, which has proved successful for HTML based search on the Web, is made available for Grid services, it will serve as a powerful tool for scientists to retrieve information on resources, monitoring, replica location sets, and meta-data on scientific data sets, etc., in a seamless manner. To enable this vision, there is a critical need to design and develop tools that abstract away the fundamental complexity of XML based Grid specifications and toolkits, and provide an elegant, intuitive, simple, and powerful free-form query based invocation system to end users. Current implementations of XML-based Grid service descriptions require end users to have intimate knowledge of service descriptions, related toolkits, and query languages. We present our research project and initial results that employ selflearning mechanisms, matching algorithms and optimizations to match free-form user queries with corresponding operations in Grid services, and present the results to the end user. Our system uses Semantic Web concepts and Ontologies to automate discovery and matchmaking of Grid services. The research focus of this project is on the development of novel algorithms for matching user queries with correct operation names and quantifying the exact gains in accuracy due to knowledge acquisition. 1