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.

• Type: Conference
• Year: 2009
• Where: CIKM
• Authors: Adrian Popescu, Gregory Grefenstette, Pierre-Alain Moëllic
• Keywords: CIKM 2009, Database, Flickr Metadata, Image, Noisy User-supplied Metadata