Abstract
With the rapid evolution of SOA (Service Oriented Architecture) and wide techniques of web services, the web service semantic has attracted the most attention during recent years. The WS (Web Service) has become a promising technology for the development, deployment, and integration of Internet applications. The large-scale deployment of web services brings great value to web service customers; however, the large-scale, dynamic, and heterogeneous web services make it difficult to discover and compose WS. Therefore, as one of the challenges to interpreting relationships of semantics is to understand the functional associations between ontology concepts. Several approaches have been described to extract relationships between ontology concepts using term-matching methods. However, it is necessary to have flexible and efficient methods to ensure functional relationships. To facilitate the discovery the relevance of a service to a query, there are many solutions based on the use of Semantic Web technologies to develop homogeneous service descriptions to reason on and to support precise and flexible discovery. In this paper, we proposed an approach to measure semantic similarity by combining Latent Semantic Analysis Similarity (LSA) and IO-MATCHING semantic matching. The density clustering services method is treated as a pre-processing method for semantic matching between the web service and the user requirements. The results of the simulation show a high accuracy to cluster semantically web services.
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El Allali, N., Fariss, M., Asaidi, H., Bellouki, M. (2021). Towards Semantic Web Services Density Clustering Technique. In: Motahhir, S., Bossoufi, B. (eds) Digital Technologies and Applications. ICDTA 2021. Lecture Notes in Networks and Systems, vol 211. Springer, Cham. https://doi.org/10.1007/978-3-030-73882-2_49
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