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The sixth edition of the Placing Task at MediaEval introduces two new sub-tasks: (1) locale-based placing, which emphasizes the need to move away from an evaluation purely based on latitude and longitude towards an entity-centered evaluation, and (2) mobility-based placing, which addresses predicting missing locations within a sequence of movements; the(More)
In this paper, we show how the large amount of geographically annotated data in social media can be used to complement existing place databases. After explaining our method, we illustrate how this approach can be used to discover new instances of a given semantic type, using London as a case study. In particular, for several place types, our method finds(More)
The task of assigning geographic coordinates to web resources has recently gained in popularity. In particular, several recent initiatives have focused on the use of language models for georeferencing Flickr photos, with promising results. Such techniques, however, require the availability of large numbers of spatially grounded training data. They are(More)
We present a two-step approach to estimate where a given photo or video was taken, using only the tags that a user has assigned to it. In the first step, a language modeling approach is adopted to find the area which most likely contains the geographic location of the resource. In the subsequent second step, a precise location is determined within the area(More)
We explore the task of automatically assigning geographic coordinates to photos on Flickr. Using an approach based on <i>k</i>-medoids clustering and Naive Bayes classification, we demonstrate that the task is feasible, although high accuracy can only be expected for a portion of all photos. Based on this observation, we stress the importance of adaptive(More)
With the rapid adoption of GPS enabled smart phones and the fact that users are almost permanently connected to the Internet, an evolution is observed toward applications and services that adapt themselves using the user’s context, a.o. taking into account location information. To facilitate the development of such new intelligent applications, new enabling(More)
We explore the task of determining the geographic location of photos on Flickr, using combined evidence from Naive Bayes classi-fiers that are trained at different spatial resolutions. In particular, we estimate the location of Flickr photos, based on their tags, at four different scales, ranging from a city-level granularity to fine-grained intra-city(More)