Name
Abstract | ||
|---|---|---|
We 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 datato-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. (C) 2019 The Authors. Published by Atlantis Press SARL. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.2991/ijcis.d.190826.002 | INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS |
Keywords | DocType | Volume |
Natural language generation, Linguistic descriptions of data, Data-to-text, Geo-referenced data, Language grounding, Fuzzy sets | Journal | 12 |
Issue | ISSN | Citations |
2 | 1875-6891 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ramos-Soto, A. | 1 | 50 | 7.82 |
| José M. Alonso | 2 | 60 | 9.86 |
| Ehud Reiter | 3 | 2370 | 219.21 |
| Kees van Deemter | 4 | 769 | 71.23 |
| Albert Gatt | 5 | 699 | 60.78 |