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Embedding Geographic Locations for Modelling the Natural Environment Using Flickr Tags and Structured Data

  • Shelan S. JeawakEmail author
  • Christopher B. Jones
  • Steven Schockaert
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11437)

Abstract

Meta-data from photo-sharing websites such as Flickr can be used to obtain rich bag-of-words descriptions of geographic locations, which have proven valuable, among others, for modelling and predicting ecological features. One important insight from previous work is that the descriptions obtained from Flickr tend to be complementary to the structured information that is available from traditional scientific resources. To better integrate these two diverse sources of information, in this paper we consider a method for learning vector space embeddings of geographic locations. We show experimentally that this method improves on existing approaches, especially in cases where structured information is available.

Keywords

Social media Text mining Vector space embeddings Volunteered geographic information Ecology 

Notes

Acknowledgments

Shelan Jeawak has been sponsored by HCED Iraq. Steven Schockaert has been supported by ERC Starting Grant 637277.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Shelan S. Jeawak
    • 1
    • 2
    Email author
  • Christopher B. Jones
    • 1
  • Steven Schockaert
    • 1
  1. 1.School of Computer Science and InformaticsCardiff UniversityCardiffUK
  2. 2.Department of Computer ScienceAl-Nahrain UniversityBaghdadIraq

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