Spatial Co-Location Rule Mining Research in Continuous Data

Finding the co-location patterns for spatial data is a challenging problem in spatial databases. While previous work focused on the discovery of co-location patterns for categorical data, we present a novel method that finds co-location patterns in spatial continuous data. Our algorithm mines the co-location patterns for continuous data by using a multi-layer index and neighbor domain set which resembles with item-set of transactions in classical data mining. We conduct experiments with the fire data and the results indicate that the new algorithm is very effective