A Decomposition Theorem for Maximum Weight Bipartite Matchings
SIAM Journal on Computing
Semantic Matching of Web Services Capabilities
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
Collaborative Reputation Mechanisms in Electronic Marketplaces
HICSS '99 Proceedings of the Thirty-second Annual Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Semantic matchmaker with precondition and effect matching using SWRL
Expert Systems with Applications: An International Journal
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The ultimate goal of service matching is to find the service provider(s) that would perform tasks of given description with the best overall degree of satisfaction. However, service description matching solves only part of the problem. Agents that match a given request may vary greatly in their actual capabilities to perform the tasks, and an agent may have strong and weak areas. In this work, we take a quantitative approach in which performance rating is considered an integral part of an agent's capability model and service distribution is taken into account in determining the degree of match. With the dynamic refinement of the agent capability model, the broker captures an agent's performance levels as well as its strong and weak areas. An experimental system has been designed and implemented within the OWL/OWL-S framework and the results statistics show significant advantage over other major levels of brokers.