[AM10] Data mining

Algorithms have been developed to scan and search through extremely large data sets in order to find patterns within the data. These data mining and knowledge discovery techniques have been expanded to the spatial case. Legal and ethical concerns associated with such practices are considered in Knowledge Areas GS GIS and T and Society and OI Organizational and Institutional Aspects.

Introduction

External resources

• Miller, H. J. and Han, J. 2001. Geographic data mining and knowledge discovery. New York: Taylor and Francis.
  ISBN number: 9781420073980
• Yuan, M., Buttenfield, B., Gahegan, M., and Miller, H. 2004. Geospatial data mining and knowledge discovery. In R. B. McMaster and E. L. Usery Eds., A Research Agenda for Geographic Information Science, Boca Raton, Florida: CRC Press, 365-388.
  ISBN/section: 9781420038330/chapter14

Learning outcomes

• 6 - Describe how data mining can be used for geospatial intelligence
  Describe how data mining can be used for geospatial intelligence

Self assessment

Outgoing relations

• [AM10] Data mining subclassof [AM] Analytical Methods

Incoming relations

• [GC3] Artificial Intelligence and Data Mining (proposed relation) [AM10] Data mining
• [AM10-1] Problems of large spatial databases subclassof [AM10] Data mining
• [AM10-2] Data mining approaches subclassof [AM10] Data mining
• [AM10-3] Knowledge discovery subclassof [AM10] Data mining