P. Farzi; R. Akbari
Abstract
Abstract: Web service is a technology for defining self-describing objects, structural-based, and loosely coupled applications. They are accessible all over the web and provide a flexible platform. Although service registries such as Universal Description, Discovery, and Integration (UDDI) provide facilities ...
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Abstract: Web service is a technology for defining self-describing objects, structural-based, and loosely coupled applications. They are accessible all over the web and provide a flexible platform. Although service registries such as Universal Description, Discovery, and Integration (UDDI) provide facilities for users to search requirements, retrieving the exact results that satisfy users’ need is still a difficult task since providers and requesters have various views about descriptions with different explanations. Consequently, one of the most challenging obstacles in the discovery task would be how to understand both sides, which is called knowledge-based understanding. This is of immense value for search engines, information retrieval tasks, and even NPL-based various tasks. The goal is to help recognize matching degrees precisely and retrieve the most relevant services more straightforward. In this research, we introduce a conceptual similarity method as a new way that facilitates discovery procedure with less dependency on the provider and user descriptions to reduce the manual intervention of both sides and being 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 OWL-S test collection, shows that a sense-context similarity algorithm can boost the disambiguation procedure of descriptions, which leads to conceptual clarity. The proposed method improves the performance of service discovery in comparison with the novel keyword-based and semantic-based methods.
