Mining Topological Patterns in Spatio-Temporal Databases

Abstract

In this chapter, we study the problem of mining topological patterns by imposing temporal constraints into the process of mining collocation patterns. We first introduce a summary structure that summarizes the database with the instances’ count information of a feature in a region within a time window. Next, based on the summary structure, we design an algorithm, called TopologyMiner, to find the interesting topological patterns in a depth-first manner. The algorithm follows the pattern growth methodology. We also investigate an efficient way to incorporate geographical features in TopologyMiner.