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The merging procedures of two ontologies are mostly related to the enrichment of one of the input ontologies, i.e. the knowledge of the aligned concepts from one ontology are copied into the other ontology. As a consequence, the resulting new ontology extends the original knowledge of the base ontology, but the unaligned concepts of the other ontology are not considered in the new extended ontology. On the other hand, there are experts-aided semi-automatic approaches to accomplish the task of including the knowledge that is left out from the resulting merged ontology and debugging the possible concept redundancy. With the aim of facing the posed necessity of including all the knowledge of the ontologies to be merged without redundancy, this article proposes an automatic approach for merging ontologies, which is based on semantic similarity measures and exhaustive searching along of the closest concepts. The authors' approach was compared to other merging algorithms, and good results are obtained in terms of completeness, relationships and properties, without creating redundancy.

This article presents the specification of a Managing Agent of emergent serious games for a smart classroom. The Managing Agent of Emergent Serious Games is a manager of emergent serious games, which seeks to adapt emergent serious games to the subject that is developed in the smart classroom, with the aim of motivating the acquisition of knowledge and skills in students during their learning processes. The introduction of emergent serious games in a smart classroom allows incorporating a new type of teaching resource in the learning dynamic, which allows enriching with new strategies the learning process.

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