| Skip to main content | Skip to navigation |

Register Now!

A Probabilistic Approach to Spatiotemporal Theme Pattern Mining on Weblogs

  • Qiaozhu Mei, Department of Computer Science University of Illinois at Urbana-Champaign, USA
  • Chao Liu, Department of Computer Science University of Illinois at Urbana-Champaign, USA
  • Hang Su, Department of EECS Vanderbilt University, USA
  • ChengXiang Zhai, Department of Computer Science University of Illinois at Urbana-Champaign, USA

Full text:

Presentation Slides:

Track: Data Mining

Mining subtopics from weblogs and analyzing their spatiotemporal patterns have applications in multiple domains. In this paper, we define the novel problem of mining spatiotemporal theme patterns from weblogs and propose a novel probabilistic approach to model the subtopic themes and spatiotemporal theme patterns simultaneously. The proposed model discovers spatiotemporal theme patterns by (1) extracting common themes from weblogs; (2) generating theme life cycles for each given location; and (3) generating theme snapshots for each given time period. Evolution of patterns can be discovered by comparative analysis of theme life cycles and theme snapshots. Experiments on three different data sets show that the proposed approach can discover interesting spatiotemporal theme patterns effectively. The proposed probabilistic model is general and can be used for spatiotemporal text mining on any domain with time and location information.

Citation

Mei, Q., Liu, C., Su, H., and Zhai, C. 2006. A probabilistic approach to spatiotemporal theme pattern mining on weblogs. In Proceedings of the 15th International Conference on World Wide Web (Edinburgh, Scotland, May 23 - 26, 2006). WWW '06. ACM Press, New York, NY, 533-542.
DOI= http://doi.acm.org/10.1145/1135777.1135857

Organised by

ECS Logo

in association with

BCS Logo ACM Logo

Platinum Sponsors

Sponsor of The CIO Dinner


Become a sponsor or exhibitor
Valid XHTML 1.0! IFIP logo WWW Conference Committee logo Web Consortium logo Valid CSS!