Knowledgediscoveryforspatialdata-ComputerScienceVIII.pptVIP

Spatial Data Mining for Customer Segmentation Introduction: a classic example for spatial analysis A good representation is the key to solving a problem Good representation because... Represents spatial relation of objects of the same type Goals of Spatial Data Mining Identifying spatial patterns Identifying spatial objects that are potential generators of patterns Identifying information relevant for explaining the spatial pattern (and hiding irrelevant information) Presenting the information in a way that is intuitive and supports further analysis Approach to Spatial Knowledge Discovery Data Mining + Geographic Information Systems = SPIN! Representation of spatial data in Oracle Spatial A set of relations R1,...,Rn such that each relation Ri has a geometry attribute Gi or an identifier Ai such that Ri can be linked (joined) to a relation Rk having a geometry attribute Gk Geometry attributes Gi consist of ordered sets of x,y-pairs defining points, lines, or polygons Different types of spatial objects are organized in different relations  Ri (geographic layers), e.g. streets, rivers, enumeration districts, buidlings, and each layer can have its own set of attributes A1,..., An and at mostone geometry attribute G Stockport Database Schema Spatial Predicates in Oracle Spatial Typical Data Mining representation SPIN! – The Elements 1. Spatial Data Mining Platform Providing an integrated data mining platform Data access to heterogeneous and distributed data sources (Oracle RDBMS, flat file, spatial data) Organizing and documenting analysis tasks Launching analysis tasks Visualizing results SPIN! Architecture: Enterprise Java Bean-based SPIN! User Interface 2. Visual Exploratory Analyis Interactive Exploratory Analysis 3. Searching for Explanatory Patterns Data Mining Tasks in SPIN! Looking for associations between subsets of spatial and non-spatial attributes ? Spatial Association Rules A phenomenon of interest (e.