01631nas a2200205   4500000000100000000000100001008004100002260001200043653003600055653002400091653001700115100002100132700002200153245006800175856010000243300001100343490000600354520105100360022001401411       2019                            d  c12/201910aSpatial Decision Support System10aSpatial Data Mining10aSpatial OLAP1 aHamdadou Djamila1 aFarah Amina Zemri00aSOLAM: A Novel Approach of Spatial Aggregation in SOLAP Systems  uhttps://www.ijimai.org/journal/sites/default/files/files/2019/10/ijimai20195_7_10_pdf_39275.pdf  a96-1040 v53 aIn the context of a data driven approach aimed to detect the real and responsible factors of the transmission of diseases and explaining its emergence or re-emergence, we suggest SOLAM (Spatial on Line Analytical Mining) system, an extension of Spatial On Line Analytical Processing (SOLAP) with Spatial Data Mining (SDM) techniques. Our approach consists of integrating EPISOLAP system, tailored for epidemiological surveillance, with spatial generalization method allowing the predictive evaluation of health risk in the presence of hazards and awareness of the vulnerability of the exposed population. The proposed architecture is a single integrated decision-making platform of knowledge discovery from spatial databases. Spatial generalization methods allow exploring the data at different semantic and spatial scales while reducing the unnecessary dimensions. The principle of the method is selecting and deleting attributes of low importance in data characterization, thus produces zones of homogeneous characteristics that will be merged.  a1989-1660