SOLAM: A Novel Approach of Spatial Aggregation in SOLAP Systems

Author
Keywords
Abstract
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.
Year of Publication
2019
Journal
International Journal of Interactive Multimedia and Artificial Intelligence
Volume
5
Issue
Regular Issue
Number
7
Number of Pages
96-104
Date Published
12/2019
ISSN Number
1989-1660
Citation Key
URL
https://www.ijimai.org/journal/sites/default/files/files/2019/10/ijimai20195_7_10_pdf_39275.pdf
DOI
10.9781/ijimai.2019.10.002
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