This paper describes a kernel based Web Services (abbrevi-ated as service) matching mechanism for service discoveryand integration. The matching mechanism tries to exploitthe 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 thefunctional similarity between services, whose parameters arelearned by a Ranking-SVM. The experiment results showedthat several metrics for the retrieval of services have beenimproved by our approach.

Centralized UDDI currently becomes harder to catch up with the need of Internet-scale service publishing and discovery. Peer-to-peer technology with its advantages of scalability, fault-tolerance and dynamics is suitable for loose-coupled Web services' distribution in nature and prevailing nowadays. In this paper, we present a distributed, collaborative peer-to-peer service overlay suitable for service publishing and discovery based on skip graph which could be organized by planar model or tree model according to the scale of services. We propose a prefix-ordered clustering mechanism that congregates the keys within a fixed prefix into the same bucket and make the smallest one appeared as the key in the service overlay which would support prefix, range query and semantic matching on Web services. We then analyze the performance of our proposed with simulation that validates the effectiveness of the service overlay