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CIKM
2009
Springer

Mining tourist information from user-supplied collections

11 years 8 months ago
Mining tourist information from user-supplied collections
Tourist photographs constitute a large part of the images uploaded to photo sharing platforms. But filtering methods are needed before one can extract useful knowledge from noisy user-supplied metadata. Here we show how to extract clean trip related information (what people visit, for how long, panoramic spots) from Flickr metadata. We illustrate our technique on a sample of metadata and images covering 183 cities of different size and from different parts of the world. Categories and Subject Descriptors H.2.8 [Database Management]: Database applications – Data mining, Image databases; Spatial databases and GIS. General Terms Algorithms, Experimentation, Human Factors. Keywords Tourist sites, visit times, geographical gazetteer, k-Nearest Neighbors, image classification, bags of visual words, Flickr.
Adrian Popescu, Gregory Grefenstette, Pierre-Alain
Added 26 May 2010
Updated 26 May 2010
Type Conference
Year 2009
Where CIKM
Authors Adrian Popescu, Gregory Grefenstette, Pierre-Alain Moëllic
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