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2005
Springer

Analyzing Multi-level Spatial Association Rules Through a Graph-Based Visualization

9 years 8 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 that takes advantage from this taxonomic knowledge on spatial data to mine multi-level spatial association rules. A large amount of rules is typically discovered even from small set of spatial data. In this paper we present a graph-based visualization that supports data miners in the analysis of multi-level spatial association rules discovered by ARES and takes advantage from hierarchies describing the same spatial object at multiple levels of granularity. An application on real-world spatial data is reported. Results show that the use of the proposed visualization technique is beneficial.
Annalisa Appice, Paolo Buono
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where IEAAIE
Authors Annalisa Appice, Paolo Buono
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