Publicado en Expert Systems with Applications Abstract Automatic linguistic description of the available data about complex phenomena is a challenging task that is receiving the attention of data scientists in recent years. As an evolution of previous research results, there is a need of creating new linguistic computational models that allow us dealing with more complex phenomena and more complex descriptions of a growing amount of heterogeneous and real-time data. This paper contributes to this field by presenting three new ways of describing added-value information automatically extracted from data. Also, we extend previous computational models by including a description of the reliability of the available input data. Namely, we face this challenge by using a new implementation of the concept of Z-number proposed by Zadeh. We demonstrate the possibilities of the proposed extension with a practical application. The application generates automatic linguistic repor

GAVAB es un grupo multidisciplinar formado por profesores de la Universidad Rey Juan Carlos que recoge diferentes líneas de investigación encuadradas en el área de conocimiento de las Ciencias de la Computación y de la Inteligencia Artificial.