Service Discovery for Dynamic Semantic Web Service Selection

J. Li, D. Ma, L. Li, and H. Zhu (PRC)


Semantic Web Service, Service Discovery, ClusteringAlgorithm


Because of the limitations in current Web Service selection mechanism, Web Services are not used on a large-scale in real business world which calls for high robustness and trustworthiness. We propose an Agent based Adaptive Dynamic Semantic Web Service Selection framework, which is called AADSS, in which Web Service consumers can dynamically select the “right” services, and adaptively change the bound services according to the real-time conditions such as QoS properties values, service reputation ranking scores and so on. In this paper, our work focuses on a clustering based semantic web service discovery strategy for this dynamic service selection. To achieve this strategy, we present an incremental service clustering algorithm based on suffix tree clustering. We also concisely describe our prototype of the Semantic Web Service search engine.

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