Paper Info
Title
Generating geographical location descriptions with spatial templates: a salient toponym driven approach
Abstract
Natural language descriptions of geographical locations are used frequently in daily life and there is a motivation to create systems that generate such descriptions automatically, for purposes such as documentation of where events have taken place, where a person is located, where photos were taken and where plants and animals are located. Typically location descriptions combine references to named geographical features with vague spatial relational terms, such as near, north of and at that relate locations to the features. Here we describe a system for generating location descriptions, that combines spatial templates, that model the applicability of different spatial relations relative to a reference location, with toponyms in the vicinity of the described location that are selected according to aspects of salience. The toponyms are retrieved from a gazetteer service based on OpenStreetMap for which we create a hierarchical feature classification scheme to facilitate selection of toponyms according to distinctiveness of their feature types and other aspects of salience. The advantages of the approach are demonstrated in a user study, relative to an existing state of the art system and to other baseline approaches that include manually created captions and the automated methods of two widely used photo captioning systems.
Year
DOI
Venue
2022
10.1080/13658816.2021.1913498
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
Keywords
DocType
Volume
Spatial natural language, referral expressions, locative expressions, salience, landmarks, spatial preposition applicability models, vagueness, natural language generation, spatial templates, gazetteers, OpenStreetMap
Journal
36
Issue
ISSN
Citations 
1
1365-8816
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Mark M. Hall113215.77
Christopher B. Jones2106795.29