A Probabilistic Approach for Web Service Discovery

Web service discovery is a vital problem in service computing with the increasing number of services. Existing service discovery approaches merely focus on WSDL-based keyword search, semantic matching based on domain knowledge or ontologies, or QoS-based recommendations. The keyword search omits the underlying correlations and semantic knowledge or QoS information is not always available. In this paper, we propose a probabilistic service discovery approach to help web service users to retrieve related services and to improve the search performance. Specifically, we apply a probabilistic model to characterize the latten topics between services and queries, and then propose a matching method based on the topic relevance. Experiments on services from a real service repository confirm the feasibility and efficiency of this proposed method.