SOLAM: A Novel Approach of Spatial Aggregation in SOLAP Systems

TitleSOLAM: A Novel Approach of Spatial Aggregation in SOLAP Systems
Publication TypeJournal Article
Year of Publication2019
AuthorsZemri, F. A., and H. Djamila
JournalInternational Journal of Interactive Multimedia and Artificial Intelligence
ISSN1989-1660
IssueRegular Issue
Volume5
Number7
Date Published12/2019
Pagination96-104
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.

KeywordsSpatial Data Mining, Spatial Decision Support System, Spatial OLAP
DOI10.9781/ijimai.2019.10.002
URLhttps://www.ijimai.org/journal/sites/default/files/files/2019/10/ijimai20195_7_10_pdf_39275.pdf
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IJIMAI20195_7_10.pdf898.75 KB