Enhancing Spatial Association Rule Mining in Geographic Databases - Bogorny, Vania; Engel, Paulo Martins; Alvares, Luis O. (Anais do Concurso de Teses e Dissertações da SBC (CTD-SBC); 2007: Anais do XX Concurso de Teses e Dissertações, 2007)
Association rule mining algorithms generate huge amounts of patterns. In spatial association rule mining this problem increases because a significant amount of associations is well known a priori. This paper presents a novel approach for mining spatial association rules, using background knowledge. The main contributions include the use of geographic database schemas and geo-ontologies for (i) the improvement of geographic data pre-processing, (ii) the elimination of well known patterns and (iii) the generation of maximal frequent patterns without redundant and non-interesting associations.