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Generating geographical location descriptions with spatial templates: a salient toponym driven approach
International Journal of Geographical Information Science ( IF 5.7 ) Pub Date : 2021-04-26 , DOI: 10.1080/13658816.2021.1913498
Mark M. Hall 1 , Christopher B. Jones 2
Affiliation  

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.



中文翻译:

使用空间模板生成地理位置描述:一种显着的地名驱动方法

摘要

地理位置的自然语言描述在日常生活中经常使用,并且有动机创建自动生成此类描述的系统,用于记录事件发生地点、人员所在位置、照片拍摄地点和地点等目的。植物和动物都位于。通常,位置描述会将命名地理特征的引用与模糊的空间关系术语(例如nearnorth ofat)结合起来。将位置与要素相关联。在这里,我们描述了一个用于生成位置描述的系统,该系统结合了空间模板,该系统对相对于参考位置的不同空间关系的适用性进行建模,并根据显着性方面选择了所描述位置附近的地名。地名是从基于 OpenStreetMap 的地名词典服务中检索到的,我们为此创建了一个分层特征分类方案,以根据地名的特征类型的独特性和显着性的其他方面来促进地名的选择。该方法的优势在用户研究中得到证明,相对于现有的最先进系统和其他基线方法,包括手动创建的字幕和两个广泛使用的照片字幕系统的自动化方法。

更新日期:2021-04-26
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