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Enriching Taxonomies of Place Types Using Flickr

  • Conference paper
Foundations of Information and Knowledge Systems (FoIKS 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8367))

Abstract

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 P 1,...,P n have a given property, we could then induce that all places which are located in the convex hull of {P 1,...,P n } 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.

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Author information

Authors and Affiliations

  1. School of Computer Science & Informatics, Cardiff University, 5 The Parade, CF24 3AA, Cardiff, United Kingdom

    Joaquín Derrac & Steven Schockaert

Authors
  1. Joaquín Derrac
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  2. Steven Schockaert
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Editors and Affiliations

  1. Fakultät für Mathematik und Informatik, FernUniversität in Hagen, Universitätstrasse 1, 58084, Hagen, Germany

    Christoph Beierle

  2. Istituto di Scienza e Tecnologie della Informazione, Consiglio Nazionale delle Ricerche, Via G. Moruzzi 1, 56124, Pisa, Italy

    Carlo Meghini

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Derrac, J., Schockaert, S. (2014). Enriching Taxonomies of Place Types Using Flickr. In: Beierle, C., Meghini, C. (eds) Foundations of Information and Knowledge Systems. FoIKS 2014. Lecture Notes in Computer Science, vol 8367. Springer, Cham. https://doi.org/10.1007/978-3-319-04939-7_8

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  • DOI: https://doi.org/10.1007/978-3-319-04939-7_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-04938-0

  • Online ISBN: 978-3-319-04939-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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