Representations of geographic regions play a decisive role in geographic information retrieval, where the query is specified by a conceptual part and a geographic part. One aspect is to use them as query footprint which is then applied for the geographic ranking of documents. Users often specify textual descriptions of geographic regions that are not contained in the underlying gazetteer or geographic database. Approaches that automatically determine a geographic footprint for those locations have a strong need for measuring the quality of this footprint, for evaluation as well as for automatical parameter learning. This quality is determined by the ’similarity’ between the footprint and a correct representation of that region.
In this paper we introduce three domain-specific points of view for measuring the similarity between representations of geographic regions for geographic information retrieval. For each point of view (strict similarity, visual similarity and similarity in ranking) we introduce a dedicated measure, two of which are novel measures that we propose in this paper.