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IEAAIE
2005
Springer
13 years 11 months ago
Analyzing Multi-level Spatial Association Rules Through a Graph-Based Visualization
Association rules discovery is a fundamental task in spatial data mining where data are naturally described at multiple levels of granularity. ARES is a spatial data mining system ...
Annalisa Appice, Paolo Buono
ICDE
2006
IEEE
130views Database» more  ICDE 2006»
14 years 7 months ago
MIC Framework: An Information-Theoretic Approach to Quantitative Association Rule Mining
We propose a framework, called MIC, which adopts an information-theoretic approach to address the problem of quantitative association rule mining. In our MIC framework, we first d...
Yiping Ke, James Cheng, Wilfred Ng
KDD
1998
ACM
146views Data Mining» more  KDD 1998»
13 years 10 months ago
Mining Association Rules in Hypertext Databases
In this workweproposea generalisation of the notion of associationrule in the contextof flat transactions to that of a compositeassociation rule in the context of a structured dir...
José Borges, Mark Levene
EDBT
2008
ACM
160views Database» more  EDBT 2008»
13 years 7 months ago
Taxonomy-superimposed graph mining
New graph structures where node labels are members of hierarchically organized ontologies or taxonomies have become commonplace in different domains, e.g., life sciences. It is a ...
Ali Cakmak, Gultekin Özsoyoglu
KAIS
2008
119views more  KAIS 2008»
13 years 5 months ago
An information-theoretic approach to quantitative association rule mining
Abstract. Quantitative Association Rule (QAR) mining has been recognized an influential research problem over the last decade due to the popularity of quantitative databases and th...
Yiping Ke, James Cheng, Wilfred Ng