Análisis de la Influencia de las Propiedades Semánticas en los Sistemas de Recomendación

Kenneth Samuel Palacio Baus, Mauricio Espinoza Mejía, Victor Saquicela, Humberto Albán, Johnny Ávila, Xavier Riofrío

Resumen


Resumen:Este artículo propone un procedimiento para la evaluación del impacto que tiene la inclusión de determinadaspropiedades semánticas y sus combinaciones en la estimación de recomendaciones de contenidos audiovisuales,generadas por un sistema de recomendación semántico para usuarios en el domino de la Televisión Digital. Este trabajo parte de la hipótesis de que el incremento moderado del número de propiedades involucradas en el cálculo delas predicciones mejora paulatinamente su precisión y que cada propiedad semántica tiene una influencia específica.Los resultados experimentales demuestran que el uso de diferentes combinaciones de propiedades semánticas, tiende areducir el error promedio en distinta proporción.

 

Abstract: This paper presents an evaluation procedure focused on analyzing the impact of the inclusion of determinedsemantic properties and their combinations, on the audiovisual content recommendation estimation performed by asemantic recommender system to users in the domain of Digital Television. This work is based on the assumption that byincreasing the number of semantic properties involved in the prediction estimation, its accuracy will be improved giventhat each semantic property has a determined influence. The obtained results show that the use of different semanticproperties combinations leads, in general, to a specific reduction of the average estimation error

 


Citas


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