Uma abordagem para descoberta, composição e Invocação Automática de Serviços semânticos aplicada ao Domínio de Mineração de dados

Abstract

The development of applications based on Semantic Web Services has evolved and gained special attention from both academia and industry. Essentially, they have been used to enable and automate tasks that involve aspects such as: discovery, composition, and automatic invocation of services. For this, the community has been dedicated in the creation of semantic models and tools that are able to explore the semantic concepts of the services. In this context, the work in question proposes a Framework based on Semantic Web Services applied to the domain of Educational Data Mining based on a new semantic model that supports the process of discovery, composition and invocation in an automatic and dynamic way. To this end, semantic services encapsulate techniques and algorithms for mining, pre-processing and post-processing of data. In order to evaluate the proposed framework, we performed an experiment based on scenarios that simulate the execution of the proposed solution in a real environment with the intention of evaluating the attributes of quality performance and reliability.