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ISMIS
2005
Springer
14 years 3 months ago
Mining and Filtering Multi-level Spatial Association Rules with ARES
In spatial data mining, a common task is the discovery of spatial association rules from spatial databases. We propose a distributed system, named ARES that takes advantage of the ...
Annalisa Appice, Margherita Berardi, Michelangelo ...
PKDD
2004
Springer
141views Data Mining» more  PKDD 2004»
14 years 3 months ago
Spatial Associative Classification at Different Levels of Granularity: A Probabilistic Approach
In this paper we propose a novel spatial associative classifier method based on a multi-relational approach that takes spatial relations into account. Classification is driven by s...
Michelangelo Ceci, Annalisa Appice, Donato Malerba
BMCBI
2010
113views more  BMCBI 2010»
13 years 10 months ago
ProbABEL package for genome-wide association analysis of imputed data
Background: Over the last few years, genome-wide association (GWA) studies became a tool of choice for the identification of loci associated with complex traits. Currently, impute...
Yurii S. Aulchenko, Maksim V. Struchalin, Cornelia...
SIGMOD
1997
ACM
134views Database» more  SIGMOD 1997»
14 years 2 months ago
Scalable Parallel Data Mining for Association Rules
One of the important problems in data mining is discovering association rules from databases of transactions where each transaction consists of a set of items. The most time consu...
Eui-Hong Han, George Karypis, Vipin Kumar
ADVIS
2004
Springer
14 years 3 months ago
Incremental Association Rule Mining Using Materialized Data Mining Views
Data mining is an interactive and iterative process. Users issue series of similar queries until they receive satisfying results, yet currently available data mining systems do not...
Mikolaj Morzy, Tadeusz Morzy, Zbyszko Króli...