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» Join Indices as a Tool for Spatial Data Mining
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132
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TSDM
2000
189views Data Mining» more  TSDM 2000»
15 years 2 months ago
Join Indices as a Tool for Spatial Data Mining
The growing production of maps is generating huge volume of data stored in large spatial databases. This huge volume of data exceeds the human analysis capabilities. Spatial data m...
Karine Zeitouni, Laurent Yeh, Marie-Aude Aufaure
73
Voted
URBAN
2008
62views more  URBAN 2008»
14 years 10 months ago
Performance Indicators a tool to Support Spatial Data Infrastructure assessment
Garfield A. Giff, Joep Crompvoets
70
Voted
IIS
2004
15 years 8 days ago
Query Selectivity Estimation via Data Mining
Estimating the result size of a join is an important query optimization problem as it determines the choice of a good query evaluation strategy. Yet, there are few efficient techni...
Jarek Gryz, Dongming Liang
116
Voted
ICDM
2005
IEEE
149views Data Mining» more  ICDM 2005»
15 years 4 months ago
A Join-Less Approach for Co-Location Pattern Mining: A Summary of Results
Spatial co-location patterns represent the subsets of features whose instances are frequently located together in geographic space. Co-location pattern discovery presents challeng...
Jin Soung Yoo, Shashi Shekhar, Mete Celik
SIGMOD
1997
ACM
113views Database» more  SIGMOD 1997»
15 years 2 months ago
Size Separation Spatial Join
The Partitioned Based Spatial-Merge Join (PBSM) of Patel and DeWitt and the Size Separation Spatial Join (S3 J) of Koudas and Sevcik are considered to be among the most efficient ...
Nick Koudas, Kenneth C. Sevcik