Francisco Javier Rodríguez-Martínez

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The amount of research papers published nowadays related to ontology matching is remarkable and we believe that reflects the growing interest of the research community. However, for new practitioners that approach the field, this amount of information might seem overwhelming. Therefore, the purpose of this work is to help in guiding new practitioners get a(More)
In this paper we describe a novel proposal in the field of smart cities: using an ontology matching algorithm to guarantee the automatic information exchange between the agents and the smart city. A smart city is composed by different types of agents that behave as producers and/or consumers of the information in the smart city. In our proposal, the data(More)
In recent years, the quality of Phrase-Based Statistical Machine Translation has increased dramatically partially due to the significant increase of available parallel corpus. If we talk in terms of space, this advantage becomes a disadvantage because the increased size of the parallel corpus implies an exponential increase in the size of the translation(More)
In this paper we propose the use of an ontology matching algorithm to guarantee the interoperability of the different agents that integrate an smart city. In this sort of environment the different parties need to cooperate and to integrate their information in order to provide enhanced services to the users of the smart city. As the information of these(More)
In this paper, we made a state of the art about the Ontology matching algorithms and we propose a general classification of them. A selection of three algorithms to work with a concrete platform is presented:CODI, LogMap and MaasMatch. We propose a testbed to evaluate the algorithms divided in three groups of tests. The algorithms were tested and evaluated(More)