Abstract
Automatic generation of natural language is a challenging multidisciplinary research field. This paper presents some first results in the NATCONSUMERS European project. The goal of this project is the generation of natural language recommendations that are tailored to each specific consumer characteristics for promoting more sustainable behaviors of consumption.
Here, we present a multidisciplinary research that consists in merging a classical architecture for natural language generator systems, proposed in the field of Computational Linguistics, together with results of our previous research in the field of Computing with Perceptions. We present a general view of the architecture of the NATCONSUMERS natural language generator system and we include an example of implementation.
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Acknowledgments
We thank our partners in NATCONSUMERS project for their help in performing this research. We thank especially our Hungarian partners Ariosz ltd. that have provided us with the data base and the classification of consumers that we have used in this first work. This project has received funding from the European Union Horizon 2020 research and innovation program under grant agreement No 657672. Also this research was partially funded by the Spanish Ministry of Economy and Competitiveness under project TIN2014-56633-C3-1-R.
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Trivino, G., Sanchez-Valdes, D. (2015). Generation of Linguistic Advices for Saving Energy: Architecture. In: Dediu, AH., Magdalena, L., Martín-Vide, C. (eds) Theory and Practice of Natural Computing. TPNC 2015. Lecture Notes in Computer Science(), vol 9477. Springer, Cham. https://doi.org/10.1007/978-3-319-26841-5_7
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DOI: https://doi.org/10.1007/978-3-319-26841-5_7
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