کشف معنایی از خدمات وب از طریق یادگیری اجتماعی

The increasing numbers of web services impose automatic discovery process in Service Oriented Architecture (SOA). But the existing SOA enables only syntactic discovery which produces coarse irrelevant results or sometimes no results. Different researches challenge this problem by introducing semantic discovery process in SOA to enable relevant and desired search results. These research outcomes cannot discover services effciently which are created independently with different knowledge bases. To overcome these problems, a new architecture of SOA is proposed which incorporates a new adaptive technique called social learning that improves service provider's domain ontology from service consumer's concept contributions and thus eventually makes the service more semantically discoverable. The proposed architecture contains new similarity measure and automatic merging algorithms on weighted ontology. From mathematical reasoning it is induced that the proposed architecture reduces overlapping concepts and thus more relevant discovery results are ensured. To test the proposed architecture's performance, a prototype of Universal Description Discovery and Integration (UDDI) is implemented and a simulation is conducted with real data set of OWL-S Technical Chart (OWLS-TC). About 67% noise responses from syntactic search (N-Gram String Distance algorithm) are reduced in the proposed architecture. The results also illustrate the proposed architecture's capabilities of concept learning and so about significant improvement in service discovery after a few social concept contributions.

The web has been evolving into the world’s largest distributed system for sharing information. The growth of web and wide acceptance of web protocols in different systems makes the hype of Service Oriented Architecture (SOA) popularly known as web service [1]. In SOA, a service provider exposes its services in standardWeb Service Description Language (WSDL). From theWSDL specification the service consumer can make software clients to consume the service. The interacting messages are carried in SOAP as payload of different web protocols like HTTP, SMTP etc

Service oriented architecture (SOA) is the face of new generation web and is going to experience an explosive growth because of it’s automated nature and high productivity in information technology. The success of SOA hugely depends on efficient automatic discovery process which enables service invocation and composition automatically in consequences. SOA becomes more efficient if it can produce more accurate and desired discovery results. In this paper, a new architecture of SOA is proposed which enables semantic discovery of web services with an adaptive learning technique termed as social learning which produces more relevant discovery results over times. The ontology of the service provider improves it’s concept through social concept contributions of service consumers and thus it becomes more discoverable over times. Through mathematical reasoning and experimental results it is shown that the concept matching and merging processes of the proposed architecture reduce noisy results of existing syntactic discovery processes significantly. The matching and merging processes in the architecture can be treated as a guideline for further researchers on adaptive learning in SOA