Adaptive middle agents for service matching
Tim Finin, 10:51pm 10 November 2004Xiaocheng Luan’s Ph.D. disseration on a quantitative approach to matching service requests against capability descriptions is now available on line.
Xiaocheng Luan, Adaptive Middle Agent for Service Matching in the Semantic Web: A Quantitative Approach, Ph.D. dissertation, Computer Science and Electrical Engineering, University of Maryland, Baltimore County, November 01, 2004.
In Dr. Luan’s approach, middle agents establish and refine an agent’s capability model based on the domain ontology and through the interactions with the agents. An agent’s performance history is considered as an integral part of the agent’s capability model and the agent’s strong and weak areas can also be revealed. The dynamically captured and updated service distribution in the service domain is considered as an important factor in service matching. Service matching here is carried out in two steps. In the first step, candidates are selected through the semantic service description matching. In the second step, the performance rating of each candidate with respect to the specific request is estimated based on the agent’s capability model, and the candidates with the highest estimated performance ratings will be selected. Statistics collected from evaluation experiments show a significant improvement over typical service matching methods in terms of the accuracy in selecting the best service provider(s) for each request.
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