Clustering of Web Services Based on WordNet Semantic Similarity

Abstract

As service-oriented architecture is getting popular, vast numbers of web services have been developed over a broad range of functionalities. It becomes a challenging task to find the relevant or similar web services using web services registry such as UDDI manually. Current UDDI search uses keywords from web service and company information in its registry to retrieve web services. This information cannot fully capture user’s needs and may miss out on potential matches. Underlying functionality and semantics of web services need to be considered. In this paper, we explore semantics of web services using WSDL operation names and parameter names along with WordNet. We compute semantic similarity of web services and use this data to generate clusters. Then, we use a novel approach to represent the clusters and utilize that information to further predict similarity of any new web services. This approach has yielded good results and it can be efficiently used by web service search engines to retrieve similar or related web services.