# Leveraging Knowledge from the Linked Open Data Cloud in the task of Reverse Geo-tagging

* Corresponding author
1 DRIM - Distribution, Recherche d'Information et Mobilité
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : Currently, Reverse Geo-tagging relies on the keywords describing an image and use probabilistic algorithms to guess the localization of the depicted scene. However, such algorithms still perform poorly and show clear limitations Notably, the location estimation only occurs at the landmark level; regions or countries are only processed through their centroid. In this paper, we address this particular issue by exploring a semantic approach, which identifies geographical entities among the keywords to localize the picture (being a landmark or a country). We leverage the Linked Open Data cloud to find possible entities. The benefits of our approach, as opposed to numerical approaches, include an in-depth study of the geo-relevance'' of an image.
Keywords :
Document type :
Conference papers

https://hal.archives-ouvertes.fr/hal-01159391
Contributor : Elöd Egyed-Zsigmond <>
Submitted on : Wednesday, June 3, 2015 - 11:21:22 AM
Last modification on : Tuesday, June 1, 2021 - 2:08:07 PM

### Identifiers

• HAL Id : hal-01159391, version 1

### Citation

Elöd Egyed-Zsigmond, Harald Kosch, Victor Charpenay. Leveraging Knowledge from the Linked Open Data Cloud in the task of Reverse Geo-tagging. Inforsid, May 2015, Biarritz, France. pp.115-130. ⟨hal-01159391⟩

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