Enriching Taxonomies of Place Types Using Flickr

Place types taxonomies tend to have a shallow structure, which limits their predictive value. Although existing place type taxonomies could in principle be refined, the result would inevitably be highly subjective and application-specific. Instead, in this paper, we propose a methodology to enrich place types taxonomies with a ternary betweenness relation derived from Flickr. In particular, we first construct a semantic space of place types by applying dimensionality reduction methods to tag co-occurrence data obtained from Flickr. Our hypothesis is that natural properties of place types should correspond to convex regions in this space. Specifically, knowing that places P1, ..., Pn have a given property, we could then induce that all places which are located in the convex hull of {P1, ..., Pn} in the semantic space are also likely to have this property. To avoid relying on computationally expensive convex hull algorithms, we propose to derive a ternary betweenness relation from the semantic space, and to approximate the convex hull at the symbolic level based on this relation. We present experimental results which support the usefulness of our approach.