Albacete García, EsperanzaCalle Gómez, Francisco JavierCastro Galán, ElenaCuadra Fernández, María Dolores2015-03-102015-03-102012-07Journal of Artificial Intelligence Research 44 (2012) 397-4211076-9757https://hdl.handle.net/10016/20226The focus of this paper is the calculation of similarity between two concepts from an ontology for a Human-Like Interaction system. In order to facilitate this calculation, a similarity function is proposed based on five dimensions (sort, compositional, essential, restrictive and descriptive) constituting the structure of ontological knowledge. The paper includes a proposal for computing a similarity function for each dimension of knowledge. Later on, the similarity values obtained are weighted and aggregated to obtain a global similarity measure. In order to calculate those weights associated to each dimension, four training methods have been proposed. The training methods differ in the element to fit: the user, concepts or pairs of concepts, and a hybrid approach. For evaluating the proposal, the knowledge base was fed from WordNet and extended by using a knowledge editing toolkit (Cognos). The evaluation of the proposal is carried out through the comparison of system responses with those given by human test subjects, both providing a measure of the soundness of the procedure and revealing ways in which the proposal may be improved.25application/pdfeng© 2012 AI Access Foundationresearch articleInformáticadoi:10.1613/jair.3612open access397421Journal of Artificial Intelligence Research44AR/0000010150