Spatial co-location pattern discovery (SCPD), a kind of knowledge discovery process, aims at discovering potentially unknown co-location patterns (co-locations). Co-locations have been widely used in many aspects, including life services, ecological environment, business research, etc. Many methods have been proposed to discover co-locations. However, these methods only discovered co-locations consisting of fine-grain spatial features, since the user knowledge is ignored, many interesting and general patterns are still undiscovered. Meanwhile, co-locations that are discovered by current frameworks are quantity-numerous and independent; thus, their usefulness is strongly limited. To overcome these shortcomings, this paper introduces the user knowledge into the process of SCPD, to discover general and intrinsic co-locations and help users quickly find their interested patterns. First, a framework OCPM (Co-location Pattern Miner using Ontology) is proposed, where an ontology is employed to integrate user knowledge to guide the process of SCPD. Second, a new co-location consisting of ontology concepts is proposed. Under the guidance of the ontology, we propose the prevalent semantic multi-level co-locations (PSMCs) consisting of ontology concepts to represent richer knowledge. Third, we design two different ways, i.e., the Apriori-like and clique-based ways, to meet the requirements of OCPM and propose a novel clique-based algorithm named IDG to discover PSMCs. Meanwhile, a top-down search strategy is proposed to help users quickly find interesting knowledge via the ontology. Finally, we validate OCPM and IDG on both real and synthetic datasets, respectively, the experimental results demonstrate their effectiveness.
