Asian Journal of Information Technology

Year: 2012
Volume: 11
Issue: 3
Page No. 94 - 99

STEM: A Novel Approach for Spatiotemporal Sequence Mining

Authors : Kelvin Leong and Stephen Chan

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.

How to cite this article:

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

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