SDMOQL: An OQL-based Data Mining Query Language for Map Interpretation Tasks
Donato Malerba, Annalisa Appice, Nicola Vacca · 2002
Spatial data mining denotes the extraction of patterns from both spatial and aspatial data, possibly stored in a spatial database. An important application of spatial data mining methods is the extraction of knowledge from a Geographic Information System. INGENS (Inductive Geographic Information System) is a prototype GIS which integrates data mining tools to assist users in their task of topographic map interpretation. The system can mine geographical concepts that are not explicitly available in the database. The spatial data mining process is aimed at a user who controls the parameters of the process by means of a mining query written in a mining query language. This paper presents SDMOQL, a spatial mining query language, based on the standard OQL, which permits the specification of the task-relevant data, the kind of knowledge to be mined, the background knowledge and the hierarchies, and the interestingness measures. SDMOQL currently supports two data mining tasks in INGENS: inducing classification rules and discovering association rules.