Mining and Filtering Multi-level Spatial Association Rules with ARES

Abstract

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 use of a multi-relational approach to mine spatial association rules. It supports spatial database coupling and discovery of multi-level spatial association rules as a means for spatial data exploration. We also present some criteria to bias the search and to filter the discovered rules according to user’s expectations. Finally, we show the applicability of our proposal to two different real world domains, namely, document image processing and geo-referenced analysis of census data.KeywordsAssociation RuleDocument ImageSpatial DatabaseAssociation Rule MiningGranularity LevelThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.