Resumen. El ser humano se comunica y expresa a través del lenguaje. Para conseguirlo, ha de desarrollar una serie de habilidades de alto nivel cognitivo cuya complejidad se pone de manifiesto en la tarea de automatizar el proceso, tanto cuando se trata de producir lenguaje como de interpretarlo. Cuando la acción comunicativa ocurre entre una persona y un ordenador ý esteúltimo es el destinatario de la acción, se emplean lenguajes computacionales que, como norma general, están sujetos a un conjunto de reglas fuertemente tipadas, acotadas y sin ambigüedad. Sin embargo, cuando el sentido de la comunicación es el contrario y la máquina ha de transmitir información a la persona, si el mensaje se quiere transmitir en lenguaje natural, el procedimiento para generarlo debe lidiar con la flexibilidad y la ambigüedad que lo caracterizan, dando lugar a una tarea de alto nivel de complejidad. Para que las máquinas sean capaces de manejar el lenguaje humano se hacen necesarias técnicas de Lingüística Computacional. Dentro de esta disciplina, el campo que se encarga de crear textos en lenguaje natural se denomina Generación de Lenguaje Natural (GLN). En este artículo se va a hacer un recorrido exhaustivo de este campo. Se describen las fases en las que se suelen descomponer los sistemas de GLN junto a las técnicas que se aplican y se analiza con detalle la situación actual de estaárea de investigación y su problemática, así como los recursos más relevantes y las técnicas que se están empleando para evaluar la calidad de los sistemas.Palabras clave. Lingüística computacional, generación de lenguaje natural, GLN, fases, técnicas, evaluación. Natural Language Generation: Revision of the State of the ArtAbstract. Language is one of the highest cognitive skills developed by human beings and, therefore, one of the most complex tasks to be faced from the computational perspective. Human-computer communication processes imply two different degrees of difficulty depending on the nature of that communication. If the language used is oriented towards the domain of the machine, there is no place for ambiguity since it is restricted by rules. However, when the communication is in terms of natural language, its flexibility and ambiguity becomes unavoidable. Computational Linguistic techniques are mandatory for machines when it comes to process human language. Among them, the area of Natural Language Generation aims to automatical development of techniques to produce human utterances, text and speech. This paper presents a deep survey of this research area taking into account different points of view about the theories, methodologies, architectures, techniques and evaluation approaches, thus providing a review of the current situation and possible future research in the field. Keywords.Computational linguistics, natural language generation, NLG, stages, techniques, evaluation. IntroducciónLa Lingüística Computacional (LC) es un campo en el que convergen diversas disciplinas: la lingüística aplicada, la informática y la inteligencia artifici...
On-line Social Networks have increased their popularity rapidly since their creation, providing a huge amount of data which can be leverage to extract useful information related to commercial and social human behaviours. One of the most useful information that can be extracted is the geographical one. This paper shows an approach to detect the geographical focus of Twitter users at city level based on the text of the tweets that users have sent and external information from Wikipedia. The main goal of this work is to show how important could be external formal text resources such as Wikipedia when it comes to resolve the geographical focus in short pieces of informal natural language text. In order to accomplish this objective, we have assessed our system with a language model system, comparing the results using only the informal pieces of text (tweets) and merging it with formal text coming from Wikipedia. In our experiments, we found that the aid of formal pieces of text, such as those obtained from the Wikipedia articles and links, could be useful when the existing amount of data is rather limited.
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