Deducing Trip Related Information from Flickr

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Abstract

Uploading tourist photos is a popular activity on photo sharing platforms. These photographs and their associated metadata (tags, geo-tags, and temporal information) should be useful for mining information about the sites visited. However, user-supplied metadata are often noisy and efficient filtering methods are needed before extracting useful knowledge. We focus here on exploiting temporal information, associated with tourist sites that appear in Flickr. From automatically filtered sets of geo-tagged photos, we deduce answers to questions like “how long does it take to visit a tourist attraction?” or “what can I visit in one day in this city?” Our method is evaluated and validated by comparing the automatically obtained visit duration times to manual estimations.