Alejandro Ramos-Soto

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Abstract—We present in this paper an application which automatically generates textual short-term weather forecasts for every municipality in Galicia (NW Spain), using the real data provided by the(More)
In this paper we present a fuzzy automatic approach for the building of linguistic descriptions of meteorological data in the realms of operative forecasting and monthly climate reports. Our results have been checked experimentally against the forecasts and reports issued by the Galician Meteorological Service (Meteogalicia), showing that the produced(More)
—In this paper we present the SoftLearn Activity Reporter (SLAR) service which automatically generates textual short-term reports about learners' behavior in virtual learning environments. Through this approach, we show how textual reporting is a coherent way of providing information that can complement (and even enhance) visual statistics and help teachers(More)
Important advances have been made in the fuzzy quantification field. Nevertheless, some problems remain when we face the decision of selecting the most convenient model for a specific application. In the literature, several desirable adequacy properties have been proposed, but theoretical limits impede quantification models from simultaneously fulfilling(More)
This paper describes the contributions of the SoftLearn platform to key issues in learning analytics, as i) discovery of the learning path that students follow in a course and ii) provide interpretability of graphs in dashboards 1 System's Purpose SoftLearn is a process mining-based platform that identifies and highlights all the content generated by the(More)