A Fully Automatic Approach to the Semantic Annotation of Web Service Descriptions

The definition and use of a semantic layer in Web Services (WS) descriptions is a prerequisite to the automation of several important operations such as WS composition and discovering. For this reason, in the past years, many approaches have been proposed to either represent such high level information, or take advantage of it. In order to be properly tested and compared, these tools must be applied to an appropriate benchmark, taking the form of a collection of semantic WS descriptions. However, all of the existing publicly available collections are limited in terms of size or realism, leading to unreliable results. Large real-world syntactic (WSDL) collections exist, so an appropriate benchmark could be obtained through their semantic annotation. Due to the number of operations to process, performing this task manually would be costly in terms of time and efforts, though. A better solution would therefore be to use an automatic tool. The software mataws was precisely designed for this purpose. However, it suffers from certain limitations. In this work, we propose some modifications aiming at solving them. The resulting tool takes advantage of the latent semantics present not only in the parameter names, but also in the type names and structures. Concept-to-word association is performed by using Sigma, a mapping of WordNet to the SUMO ontology. After having described in details our annotation method, we apply it to the largest collection of real-world syntactic WS descriptions we could find, and assess its efficiency