An Efficient Hybrid Method for Semantic Web Service Discovery

The web service is a technology for defining the self-describing objects, and the structural-based and loosely coupled applications. They are accessible all over the web, and provide a flexible platform. Although the service registries such as Universal Description, Discovery and Integration (UDDI) provide facilities for the users in oder to search for the requirements, retrieving the exact results that satisfy the users‟ needs is still a difficult task since the providers and requesters have various views about the descriptions with different explanations. Consequently, one of the most challenging obstacles involved in the discovery task would be how to understand both sides, which is called the knowledge-based understanding. This is of immense value for the search engines, information retrieval tasks, and even NLP-based various tasks. The goal is to help recognize the matching degrees precisely and retrieve the most relevant services more straightforward. In this research work, we introduce a conceptual similarity method as a new way that facilitates the discovery procedure with a less dependency on the provider and the user descriptions to reduce the manual intervention of both sides and is more explicit for the machines. We provide a comprehensive knowledge-based approach by applying the Latent Semantic Analysis (LSA) model to the ontology scheme-WordNet and domain-specific in-sense context-based similarity algorithm. The evaluation of our similarity method, done on the OWL-S test collection, shows that a sense-context similarity algorithm can boost the disambiguation procedure of descriptions, which leads to a conceptual clarity. The proposed method improves the performance of service discovery in comparison with the novel keyword-based and semantic-based methods.