Reliable Spatio-temporal Signal Extraction and Exploration from Human Activity Records

  • Christian Sengstock
  • Michael Gertz
  • Hamed Abdelhaq
  • Florian Flatow
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8098)

Abstract

Shared multimedia, microblogs, search engine queries, user comments, and location check-ins, among others, generate an enormous stream of human activity records. Such records consist of information in the form of text, images, or videos, and can often be traced in time and space using associated time/location information. Over the past years such spatio-temporal activity streams have been heavily studied with the aim to extract and explore spatio-temporal phenomena, like events, place descriptions, and geographical topics. Despite the clear intuition and often simple techniques to extract such knowledge, the amount of noise, sparsity, and heterogeneity in the data makes such tasks non-trivial and erroneous. This demonstration offers a visual interface to compare, combine, and evaluate spatio-temporal signal extraction and exploration approaches from large-scale sets of human activity records.

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References

  1. 1.
    Rattenbury, T., Naaman, M.: Methods for Extracting Place Semantics from Flickr Tags. ACM Transactions on the Web 3(1), 1–30 (2009)CrossRefGoogle Scholar
  2. 2.
    Xu, J.-M., Bhargava, A., Nowak, R., Zhu, X.: Socioscope: Spatio-temporal Signal Recovery from Social Media. In: Flach, P.A., De Bie, T., Cristianini, N. (eds.) ECML PKDD 2012, Part II. LNCS, vol. 7524, pp. 644–659. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  3. 3.
    Sakaki, T., Okazaki, M., Matsuo, Y.: Earthquake Shakes Twitter Users: Real-time Event Detection by Social Sensors. In: Proc. of WWW 2010, pp. 851–860 (2010)Google Scholar
  4. 4.
    Yin, Z., Cao, L., Han, J., Zhai, C., Huang, T.: Geographical Topic Discovery and Comparison. In: Proc. of WWW 2011, pp. 247–256 (2011)Google Scholar
  5. 5.
    Zhang, H., Korayem, M., You, E., Crandall, D.J.: Beyond Co-occurrence: Discovering and Visualizing Tag Relationships from Geo-spatial and Temporal Similarities. In: Proc. of WSDM 2012, pp. 33–42 (2012)Google Scholar
  6. 6.
    Sengstock, C., Gertz, M.: Latent Geographic Feature Extraction from Social Media. In: Proc. of GIS 2012, pp. 149–158 (2012)Google Scholar
  7. 7.
    Jin, X., Gallagher, A., Cao, L., Luo, L., Han, J.: The Wisdom of Social Multimedia: Using Flickr For Prediction and Forecast. In: Proc. of MM 2010, pp. 1235–1244 (2010)Google Scholar
  8. 8.
    Zhang, H., Korayem, M., Crandall, D.J., Lebuhn, G.: Mining Photo-sharing Websites to Study Ecological Phenomena. In: Proc. of WWW 2012, pp. 749–758 (2012)Google Scholar
  9. 9.
    Wing, B.P., Baldridge, J.: Simple Supervised Document Geolocation with Geodesic Grids. In: Proc. of ACL 2011, pp. 955–964 (2011)Google Scholar
  10. 10.
    OHare, N., Murdock, V.: Modeling Locations with Social Media. Journal of Information Retrieval 16(1), 30–62 (2012)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Christian Sengstock
    • 1
  • Michael Gertz
    • 1
  • Hamed Abdelhaq
    • 1
  • Florian Flatow
    • 1
  1. 1.Database Systems Research GroupHeidelberg UniversityGermany

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