Spatial data mining is to mine high-level spatial information and knowledge from large spatial databases. A spatial data mining system prototype, GeoMiner, has been designed and developed based on our years of experience in the research and development of relational data mining system DBMiner, and our research into spatial data mining. The data mining power of GeoMiner includes mining three kinds of rules: characteristic rules, comparison rules, and association rules, in geo-spatial databases, with a planned extension to include mining classification rules and clustering rules. The SAND (Spatial And Nonspatial Data) architecture is applied in the modeling of spatial databases, whereas GeoMiner includes the spatial data cube construction module, spatial on-line analytical processing (OLAP) module, and spatial data mining modules. A spatial data mining language, GMQL (GeoMining Query Language), is designed and implemented as an extension to Spatial SQL , for spatial data mining. Moreover an interactive, user-friendly data mining interface is constructed and tools are implemented for visualization of discovered spatial knowledge.
|Original language||English (US)|
|Number of pages||4|
|Journal||SIGMOD Record (ACM Special Interest Group on Management of Data)|
|State||Published - Jun 1997|
ASJC Scopus subject areas
- Information Systems