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Spatial data mining is the process
of discovering interesting and previously unknown, but potentially
useful patterns from large spatial datasets. Extracting interesting
and useful patterns from spatial datasets is more difficult than
extracting the corresponding patterns from traditional numeric
and categorical data due to the complexity of spatial data types,
spatial relationships, and spatial autocorrelation. This tutorial
will introduce spatial data mining in the following categories:
location prediction, spatial outlier detection, and co-location
mining.
 A General Introduction to Spatial
Data Mining
Slides:
What's Special About Spatial Data Mining?(PS,PDF)
Slides:
Spatial Data Mining: Accomplishments and Research Needs, GIScience 2004 Keynote Speech(PS,PDF)
Reference:
[SDM03] Shashi Shekhar, Pusheng
Zhang, Yan Huang, and Ranga Raju Vatsavai, "Trends in Spatial Data
Mining", as a book chapter to appear in "Data Mining:
Next Generation Challenges and Future Directions", Hillol
Kargupta and Anupam Joshi(editors), AAAI/MIT Press, 2003 (PS,
PDF)
Location Prediction
Slides:
Spatial Autoregressive Models. (PS,PDF)
Slides: Scalable Parallel Formulations
of Spatial Auto-Regression (SAR) Models for Mining Regular Grid
Geospatial Data (PPT).
Example of Scalable Parallel
Formulations of Spatial Auto-Regression (SAR) Models:
Reference:
[AHP03] Baris Kazar, Shashi
Shekhar, and David J. Lilja, "Parallel Formulation of
Spatial Auto-Regression", Army High-Performance Computing Research
Center (AHPCRC) Technical Report no. 2003-125, August 2003 (PS,
PDF)
[IEE02] S. Shekhar, P. Schrater,
R. Vatsavai, W. Wu, and S. Chawla, Spatial Contextual Classification
and Prediction Models for Mining Geospatial Data , IEEE Transactions
on Multimedia (special issue on Multimedia Dataabses) , 2002.
(PS,
PDF)
Spatial Outlier Detection
Slides: A Unified Approach to
Detecting Spatial Outliers (PS,
PDF)
Example of Spatial Outlier Detection
using Matlab:
Reference:
[GEI03] Shashi Shekhar, Chang-Tien
Lu, Pusheng Zhang, "A Unified Approach to Detecting Spatial
Outliers" volume 7, issue 2, GeoInformatica, Kluwer Academic
Publishers, 2003. (PS, PDF)
Co-location Mining
Slides: Mining Co-location Patterns
(PS, PDF)
Example of Mining Co-location
Patterns using Matlab:
Reference:
[TKD03] Yan Huang, Shashi
Shekhar, and Hui Xiong, Discovering Co-location Patterns from
Spatial Datasets: A General Approach, Submitted to IEEE TKDE(under
second round review), (PS,
PDF)
More publications are available
at the Publication
Cabinet of Spatial Databases Group
Go
Back to Spatial Databases Group Webpage
Comments on this site should be sent to Pusheng Zhang.
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