MEDIDAS DE SIMILITUD BASADAS EN CARACTERÍSTICAS PARA LA EVALUACIÓN DE RELACIONES TAXONÓMICAS (SIMILARITY MEASURES BASED ON FEATURES FOR THE EVALUATION OF TAXONOMIC RELATIONSHIPS)

Aimee Cecilia Hernández García, Mireya Tovar Vidal, José de Jesús Lavalle Martínez, Ana Patricia Cervantes Márquez

Resumen


En una ontología, la similitud semántica entre un par de conceptos es una forma de saber qué tan similares son en base a su significado, mediante el conocimiento de la distancia entre los conceptos o en base a las características de los conceptos. En esta investigación, se propone un algoritmo para la evaluación de relaciones taxonómicas en una ontología de dominio de Inteligencia Artificial (IA) a través de la medida de exactitud. Las medidas de similitud implementadas en este artículo se basan en conocimiento, y dentro de este grupo de medidas existen las medidas basadas en estructura: Path, Wu-Palmer y Li, y las medidas basadas en características: cmatch, RE y Sánchez. La exactitud de las relaciones taxonómicas de tipo “is-a” en las medidas implementadas es de un 92%. Con los resultados experimentales comparados con las respuestas de validación de un experto de dominio, el sistema coincide en un 90% de exactitud.

In an ontology, semantic similarity between a pair of concepts is a way to find out what so similar they are, this is based on their meaning by computing the distance between concepts or it is based on the characteristics of the concepts. In this paper, an algorithm is proposed for the evaluation of taxonomic relationships in a domain ontology of Artificial Intelligence (AI) through the accuracy measure. The measures of similarity implemented in this research are based on knowledge, and within this group of measures, there are measures based on structure: Path, Wu-Palmer and Li, and measures based on characteristics: cmatch, RE and Sánchez. The accuracy for the "is-a" taxonomic relationships for the measures implemented is 92%. With the experimental results compared to the validation responses of a domain expert, the system matches the 90% of accuracy.


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