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, 2019.
RankProvisionally ranked Q1 in Computer Science (all) by SJR 2018
ISSN1875-6883
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