Toward automatic generation of linguistic advice for saving energy at home

摘要: The increased demand of systems able to generate reports in natural language from numerical data involves the search for new solutions. This paper presents an adaptation standard generation methodologies customized linguistic descriptions data. Namely, we merge one most well-known architectures research field together with our previous architecture generating complex phenomena. latter is supported by computational theory perceptions which comes fuzzy sets and field. We include a practical case use dealing problem inefficient consumption energy at households. It generates recommendations adapted each household promote more responsible consumption. proposal reveals opportunities collaboration between different communities that are involved.