Ontology-based interactive post-mining of interesting co-location patterns

Abstract

Spatial co-location patterns represent the subsets of spatial features whose instances are frequently located together in geographic space. Common frameworks for mining co-location patterns generate numerous redundant colocation patterns. Thus, several methods were proposed to overcome this drawback. However, most of these methods do not guarantee that the extracted colocation patterns are interesting for the user because they are generally based on statistical information. Thus, it is crucial to help the decision-maker choose interesting co-location patterns with an efficient interactive procedure. This paper proposed an interactive approach to prune and filter discovered co-location patterns. First, ontologies were used to improve the integration of user knowledge. Second, an interactive process was designed to collaborate with the user to find the interesting co-location patterns efficiently. The experimental results on a real data set demonstrated the effectiveness of our approach.