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摘要
Geospatial clustering is an important topic in knowledge discovery research and geospatial information systems. However, current clustering research emphasizes the development of more efficient and effective clustering methods without paying much attention to domain knowledge and users' goals during the clustering process. Making better use of geospatial and clustering knowledge to select proper methods and datasets will help achieve clustering results that better meet users' requirements. In this article, we present the GEO_CLUST framework for performing geospatial clustering. The framework consists of the GeoCO ontology for geospatial clustering and the ontology reasoner reasoning mechanism. The GeoCO ontology is used to represent geospatial and clustering domain knowledge. The ontology reasoner uses classification and decomposition techniques to specify users' tasks. Using the framework, users can identify the appropriate geospatial data and clustering method based on their specific goals. To demonstrate the framework, two case studies on finding population density clusters in Western Canada and locating five hospitals in South Carolina are discussed. The results show that the framework can select the proper datasets and clustering methods with respect to users' goals.
- 出版日期2010
