Abstract
In this chapter, we incorporate utility into spatial pattern mining through the concept of pattern utility, and a general framework for spatial high utility co-location pattern mining is defined. Furthermore, we define the concepts of extended pattern utility ratio and partial extended pattern utility ratio, and present the Extended Pruning Algorithm (EPA) and Partial Pruning Algorithm (PPA) to prune down the number of candidates and obtain the complete set of spatial high utility co-location patterns. EPA and PPA improve the mining performance and accelerate the spatial high utility co-location pattern generation under different parameter environments.
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