Application of fuzzy sets in data-to-text systems

• Autores: Alejandro Ramos Soto
• Directores de la Tesis: Alberto José Bugarín Diz (dir. tes.) , Senén Barro (codir. tes.)
• Lectura: En la Universidade de Santiago de Compostela ( España ) en 2016
• Idioma: inglés
• Tribunal Calificador de la Tesis: Daniel Sánchez Fernández (presid.) , José M. Alonso Moral (secret.) , Albert Gatt (voc.)
• Enlaces
  • Tesis en acceso abierto en: MINERVA
• Resumen

  • This PhD dissertation addresses the convergence of two distinct paradigms: fuzzy sets and natural language generation. The object of study is the integration of fuzzy set-derived techniques that model imprecision and uncertainty in human language into systems that generate textual information from numeric data, commonly known as data-to-text systems. This dissertation covers an extensive state of the art review, potential convergence points, two real data-to-text applications that integrate fuzzy sets (in the meteorology and learning analytics domains), and a model that encompasses the most relevant elements in the linguistic description of data discipline and provides a framework for building and integrating fuzzy set-based approaches into natural language generation/data-to-ext systems.