Fuzzy-Based Language Grounding of Geographical References: From Writers to Readers

TítuloFuzzy-Based Language Grounding of Geographical References: From Writers to Readers
AutoresA. Ramos-Soto, Jose M. Alonso, E. Reiter, K. van Deemter, A. Gatt
TipoArtículo de revista
Fonte International Journal of Computational Intelligence Systems, Atlantis Press, Vol. 12, No. 2, pp. 970-983 , 2019.
RankProvisionally ranked Q1 in Computer Science (all) by SJR 2018
ISSN1875-6883
DOI10.2991/ijcis.d.190826.002
AbstractWe describe an applied methodology to build fuzzy models of geographical expressions, which are meant to be used for natural language generation purposes. Our approach encompasses a language grounding task within the development of an actual data-to-text system for the generation of textual descriptions of live weather data. For this, we gathered data from meteorologists through a survey and built consistent fuzzy models that aggregate the interpersonal variations found among the experts. A subset of the models was utilized in an illustrative use case, where we generated linguistic descriptions of weather maps for specific geographical expressions. These were used in a task-based evaluation to determine how well potential readers are able to identify the geographical expressions grounded on the models.
Palabras chavenatural language generation, linguistic descriptions of data, data-to-text, geo-referenced data, language grounding, fuzzy sets