Ballatore, Andrea and Bertolotto, Michela and Wilson, David C. (2014) An evaluative baseline for geo-semantic relatedness and similarity. GeoInformatica. ISSN 1384-6175

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Abstract

In geographic information science and semantics, the computation of semantic similarity is widely recognised as key to supporting a vast number of tasks in information integration and retrieval. By contrast, the role of geo-semantic relatedness has been largely ignored. In natural language processing, semantic relatedness is often confused with the more specific semantic similarity. In this article, we discuss a notion of geo-semantic relatedness based on Lehrer’s semantic fields, and we compare it with geo-semantic similarity. We then describe and validate the Geo Relatedness and Similarity Dataset (GeReSiD), a new open dataset designed to evaluate computational measures of geo-semantic relatedness and similarity. This dataset is larger than existing datasets of this kind, and includes 97 geographic terms combined into 50 term pairs rated by 203 human subjects. GeReSiD is available online and can be used as an evaluation baseline to determine empirically to what degree a given computational model approximates geo-semantic relatedness and similarity.

Item Type:	Article
Keywords:	Geo-semantic relatedness; Geo-semantic similarity; Gold standards; Geo-semantics; Cognitive plausibility; GeReSiD;
Academic Unit:	Faculty of Science and Engineering > Computer Science Faculty of Science and Engineering > Psychology
Item ID:	4757
Depositing User:	Andrea Ballatore
Date Deposited:	04 Feb 2014 11:17
Journal or Publication Title:	GeoInformatica
Publisher:	Springer
Refereed:	Yes
URI:
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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