Kelvin  Leong, Stephen  Chan, 
    STEM: A Novel Approach for Spatiotemporal Sequence Mining,
    Asian Journal of Information Technology,
    Volume 11,Issue 3,
    2012,
    Pages 94-99,
    ISSN 1682-3915,
    ajit.2012.94.99,
    (https://makhillpublications.co/view-article.php?doi=ajit.2012.94.99)
    Abstract: Building on the skeleton of Generalized Sequential Pattern 
  (GSP), researchers propose a new approach-Spatio-Temporal Events Miner (STEM) 
  for sequential pattern analysis. The STEM extends the traditional finding by 
  coverage of both temporal and spatial attributes. Furthermore, researchers are 
  interested in studying whether AprioriAll Method in traditional GSP is most 
  suitable in STEM.
    Keywords: Skelton;GSP;STEM;attributes;analysis