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X) = (2) (3) (4) The number of layers and neurons in each layer are chosen a-priori, as well as the type of activation functions for the neurons. The number of neurons in the hidden layer is usually determined by trial-and-error in order to find the simplest network that gives acceptable performance. Then, the values of the weights wj i and bias θj are initialized. These values are chosen so that the model behaves well on some set (named training set) of inputs and corresponding outputs. The process of determining the weights and thresholds is called learning or training.
Finally, Sect. 6 presents the conclusions of this chapter. 2 Foundations Semantic Web uses ontologies and a number of standard markup languages to formally model information represented in web resources so that it is accessible to humans and machines working co-operatively, perhaps with the assistance of intelligent services such as software agents, which use artificial intelligent (AI) techniques and models. The purpose of this section is to provide an introduction to some concepts that are used along the chapter, regarding Ontologies, Ontology-matching, Software Agents and Artificial Neural Networks.
Differently from the previous cited works, in [28] it is considered that labels at ontologies are human identifiers (names) for instances, normally shared by a community of humans speaking a common language inside a specific field of knowledge. It can be inferred that, if labels are the same, the instances associated to them are probably also the same or are semantically related [10]. A concept, on the other hand, can also be defined as representative of a set of instances. We can, therefore, infer that concepts that have the same instances are the same.