TY - JOUR KW - Spatial Decision Support System KW - Spatial Data Mining KW - Spatial OLAP AU - Hamdadou Djamila AU - Farah Amina Zemri AB - In 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. IS - Regular Issue M1 - 7 N2 - In 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. PY - 2019 SP - 96 EP - 104 T2 - International Journal of Interactive Multimedia and Artificial Intelligence TI - SOLAM: A Novel Approach of Spatial Aggregation in SOLAP Systems UR - https://www.ijimai.org/journal/sites/default/files/files/2019/10/ijimai20195_7_10_pdf_39275.pdf VL - 5 SN - 1989-1660 ER -