A Kernel based Structure Matching for Web Services Search
This paper describes a kernel based Web Services (abbreviated as service) matching mechanism for service discovery and integration. The matching mechanism tries to exploit the latent semantics by the structure of services. Using textual similarity and n-spectrum kernel values as features of low-level and mid-level, we build up a model to estimate the functional similarity between services, whose parameters are learned by a Ranking-SVM. The experiment results showed that several metrics for the retrieval of services have been improved by our approach.