Deducing trip related information from flickr

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.

REFERENCES

• 1: Girardin, F., Dal Fiore, F., Blat, J., Ratti, C. Understanding of Tourist Dynamics from Explicitly Disclosed Location Information. In Proc. of the 4th International Symposium on LBS and Telecartography (Hong-Kong, China, 2007).
• 2: Homeandabroad -- http://homeandabroad.com
• 3: Adrian Popescu , Gregory Grefenstette , Pierre Alain Moëllic, Gazetiki: automatic creation of a geographical gazetteer, Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries, June 16-20, 2008, Pittsburgh PA, PA, USA [doi>10.1145/1378889.1378906]
• 4: Tye Rattenbury , Nathaniel Good , Mor Naaman, Towards automatic extraction of event and place semantics from flickr tags, Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, July 23-27, 2007, Amsterdam, The Netherlands [doi>10.1145/1277741.1277762]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications
          Subjects: Data mining

General Terms:
Algorithms, Experimentation, Human Factors

Keywords:
flickr, geographical gazetteer, georeferencing, image mining, text mining, tourist sites, visit times