Jorge Martínez Gil

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In this work we present GOAL (Genetics for Ontology Alignments) a new approach to compute the optimal ontology alignment function for a given ontology input set. Although this problem could be solved by an exhaustive search when the number of similarity measures is low, our method is expected to scale better for a high number of measures. Our approach is a(More)
Due to the high costs of live research, performance simulation has become a widely accepted method of assessment for the quality of proposed solutions in this field. Additionally, being able to simulate the behavior of the future occupants of a residential building can be very useful since it can support both design-time and run-time decisions leading to(More)
Computing the semantic similarity between terms (or short text expressions) that have the same meaning but which are not lexicographically similar is an important challenge in the information integration field. The problem is that techniques for textual semantic similarity measurement often fail to deal with words not covered by synonym dictionaries. In(More)
In this work, we present our experience when developing the Matching Framework (MaF), a framework for matching ontologies that allows users to configure their own ontology matching algorithms and it allows developers to perform research on new complex algorithms. MaF provides numerical results instead of logic results provided by other kinds of algorithms.(More)
Reducing energy consumption in buildings of all kinds is a key challenge for researchers since it can help to notably reduce the waste of energy and its associated costs. However, when dealing with residential environments, there is a major problem, people comfort should not be altered, so it is necessary to look for smart methods which take into account(More)