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Abstract: Given a collection of boolean spatial features, the co-location pattern discovery process finds the subsets of features frequently located together. For example, the analysis of an ecology dataset may reveal the frequent co-location of a fire ignition source feature with a needle vegetation type feature and a drought feature. The spatial co-location rule problem is different from the association rule problem. Even though boolean spatial feature types (also called spatial events) may correspond... (Update)
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BibTeX entry: (Update)
Shashi Shekhar and Yan Huang, "Discovering Spatial Co-location Patterns: a Summary of Results," In Proc. of 7th International Symposium on Spatial and Temporal Databases (SSTD01) (2001). http://citeseer.ist.psu.edu/shekhar01discovering.html More
@article{ shekhar01discovering,
author = "Shashi Shekhar and Yan Huang",
title = "Discovering Spatial Co-location Patterns: {A} Summary of Results",
journal = "Lecture Notes in Computer Science",
volume = "2121",
pages = "236+",
year = "2001",
url = "citeseer.ist.psu.edu/shekhar01discovering.html" }
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213 Discovery of multiple-level association rules from large dat.. - Han, Fu - 1995
121 Mining Association Rules with Item Constraints - Srikant, Vu et al. - 1997
92 An Introduction to Spatial Database Systems (context) - Guting - 1994
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22 Using a Hash-Based Method with Transaction Trimming for Mini.. - Park, Chen et al. - 1997
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14 and Economic theory (context) - Krugman, Geography - 1995
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12 Turning a map into a cake layer of information (context) - Greenman - 2000
12 Geographical Information Science: Critical Issues in an Emer.. (context) - Mark - 1999
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10 A Regression Method for Spatial Disease Rates: An Estimating.. (context) - Yasui, Lele - 1997
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2 Large-scale Improverishment of Amazonian Forests by Logging .. (context) - Nepstad, Verissimo et al. - 1999
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