Oracle Data Mining
Oracle Data Mining is implemented in the Oracle Database kernel, and mining models are first class database objects.
Oracle Data Mining is an option to the Enterprise Edition of Oracle Database. It includes programmatic interfaces for SQL, PL/SQL, and Java. It also supports a spreadsheet add-in.
ODM allows automatic discovery of knowledge from a database. Its techniques include discovering hidden associations between different data attributes, classification of data based on some samples, and clustering to identify intrinsic patterns. Effective with Oracle Database 10g, spatial data can be materialized for inclusion in data mining applications. Thus, ODM might enable you to discover that sales prospects with addresses located in specific areas (neighborhoods, cities, or regions) are more likely to watch a particular television program or to respond favorably to a particular advertising solicitation. (The addresses are geocoded into longitude/latitude points and stored in an Oracle Spatial geometry object.)
In many applications, data at a specific location is influenced by data in the neighborhood. For example, the value of a house is largely determined by the value of other houses in the neighborhood. This phenomenon is called spatial correlation (or, neighborhood influence), and is discussed further in Section 8.3. The spatial analysis and mining features in Oracle Spatial let you exploit spatial correlation by using the location attributes of data items in several ways: for binning (discretizing) data into regions (such as categorizing data into northern, southern, eastern, and western regions), for materializing the influence of neighborhood (such as number of customers within a two-mile radius of each store), and for identifying colocated data items (such as video rental stores and pizza restaurants).