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.
Kelvin Leong and Stephen Chan, 2012. STEM: A Novel Approach for Spatiotemporal Sequence Mining. Asian Journal of Information Technology, 11: 94-99.