Spatial Data Mining

Marco Morais


Data mining is the automated process of discovering patterns in data. The purpose is to find correlation among different datasets that are unexpected. Supermarket chains are a prime example of entities that use data mining techniques in an effort to increase sales by trying to find correlations in consumer buying practices. In a hypothetical situation, a data miner might find a pattern that people who purchase high-end cat food also are strong purchasers of floor wax. As a result of this analysis, the supermarket might then place the pet food products in the same aisle as the household cleaners in an attempt to induce higher sales.

On-Line Transaction Processing (OLTP) is the tradional model for enterprise data processing. In OLTP, the emphasis is on transactions involving the input, update, and retrieval of data. On-Line Analytical Processing (OLAP) applications query the database to collate, summarize, and analyze its contents. Data mining augments the OLAP process by applying artificial intelligence and machine learning techniques to find previously unknown or undiscovered relationships in the data. This is different from analytical techniques in which the goal is to prove or disprove an existing hypothesis.

What is Spatial Data Mining?

Spatial data mining is the application of data mining techniques to spatial data. Spatial data mining follows along the same functions in data mining, with the end objective to find patterns in geography.

Data Mining Techniques

There are four major categories of machine learning techniques.

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  • classification
  • association
  • clustering
  • numeric prediction

Spatial Data Mining Resources


Spatial Data Mining at the University of Munich
A brief description of the subject with some links to papers.

Software Systems

GeoMiner (Site no longer active)
A prototype of a spatial data mining system. The system design includes a graphical user interface (GUI) component for data visualization, modules for performing exploratory data analysis (EDA) and spatial data mining, and a spatial database server.

Programming Resources

Java Community Process, Data Mining API
A proposed specification for standardizing the Application Programming Interface (API) used to access data mining functionality from within Java.

Oracle9i Data Mining FAQ
Frequently asked questions (FAQ) covering the data mining add-on for Oracle databases. Oracle also offers a Spatial Data Option (SDO) for their database product to enable the storage and retrieval of geographic data.

See Also

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About the author
Marco Morais