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Service-Oriented Computing (SOC) is emerging as a new promising computing paradigm. Web service discovery is one of the key issues in SOC. Web service discovery usually provide UDDI as a standard registry which features only keyword-based matches that often give poor performance. Currently approaches for semantic
Web service discovery is a vital problem in service computing with the increasing number of services. Existing service discovery approaches merely focus on WSDLbased keyword search, semantic matching based on domain knowledge or ontologies, or QoS-based recommendations. The keyword search omits the underlying
main current approaches for semantic discovery of services are the keyword-based approach and the ontology-based approach. The plain simple keyword matching strategy is time-consuming and has inefficient recall and precision. The ontology-based strategy, on the other hand, is efficient, but may not be practical for the
The number of available Web services, nowadays, is growing rapidly due their potential in many fields. As a result, the discovery process becomes a challenging issue. Traditional syntactic keywords based discovery techniques are inefficient as they fail to recognize similarities between Web services capabilities. Thus
Aiming to discover the most suitable service cater to the discovery request of service consumer which includes functional requirements and nonfunctional requirements, this paper proposes a service registry model named as SRC (Service Registry on Cloud) which is an extension of the keywords based service registry model
analyzer to pick up information of service and use keywords to find out related services; then we cluster Web services according to the similarity of services; last, we select the appropriate Web service from list of services.
propose a service discovery, which is able to discover all these new service types. In addition, it is capable to find services that are not exact matches of the requested ones. More semantics are introduced through attributes like EquivalenceClass, ParentType and Keywords.
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