Alejandro Ramos-Soto

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1063-6706 (c) 2013 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications standards/publications/rights/index.html for more information. Abstract—We present in this paper an application which automatically generates textual short-term weather forecasts for every municipality in(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 explores the current state of the task of generating easily understandable information from data for people using natural language, which is currently addressed by two independent research fields: the natural language generation field — and, more specifically, the data-to-text sub-field — and the linguistic descriptions of data field. Both(More)