Spatio-temporal Co-occurrence Pattern Mining in Data Sets with Evolving Regions

Karthik Ganesan Pillai, Rafal A. Angryk, Juan M. Banda, Michael A. Schuh, Tim Wylie
2012 2012 IEEE 12th International Conference on Data Mining Workshops  
Spatio-temporal co-occurring patterns represent subsets of event types that occur together in both space and time. In comparison to previous work in this field, we present a general framework to identify spatio-temporal cooccurring patterns for continuously evolving spatio-temporal events that have polygon-like representations. We also propose a set of measures to identify spatio-temporal co-occurring patterns and propose an Apriori-based spatio-temporal cooccurrence mining algorithm to find
more » ... valent spatio-temporal co-occurring patterns for extended spatial representations that evolve over time. We evaluate our framework on real-life data to demonstrate the effectiveness of our measures and the algorithm. We present results highlighting the importance of our measures in identifying spatio-temporal co-occurrence patterns.
doi:10.1109/icdmw.2012.130 dblp:conf/icdm/PillaiABSW12 fatcat:mlef7uqcnnc53dt6ypiny6htei