Theme Mining

Spatiotemporal Theme Pattern Mining
Mining subtopics from weblogs and analyzing their spatiotemporal (Belonging to both space and time or to space-time) patterns have applications in multiple domains. The proposed model discovers spatiotemporal theme patterns by extracting common themes from weblogs generating theme life cycles for each given location and 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 electively. The proposed probabilistic model is general and can be used for spatiotemporal text mining on any domain with time and location information.

External References
http://www.nyu.edu/classes/jcf/g22.3033-002/slides/session6/MiningFrequentPatternsAssociationAndCorrelations.pdf
http://www.terrafirma.eu.com/Documents/Workshops/WS%207/Benecke_Introduction_Mining_theme.pdf
http://sifaka.cs.uiuc.edu/czhai/pub/kdd05-ttm.pdf
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