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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Labzioui, Redouane
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Computer Science & IT Engineering

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Method for developing and partitioning graph-based data warehouses using association rules Labzioui, Redouane; Letrache, Khadija; Ramdani, Mohammed
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i1.pp810-821

Abstract

The evolution of modern databases has led to a variety of not only structured query language (NoSQL) models, particularly graph-oriented-databases. This growth has encouraged businesses to explore graph-based business intelligence (BI) solutions. This paper explores three essential aspects in the domain of graph warehouse: the establishment of efficient graph warehouses, the significance of data historization, and the development of effective strategies for graph partitioning. It starts by building a BI system within a graph database. Subsequently, the paper emphasizes the pivotal role of data historization, highlighting the slowly graph changing dimension (SGCD) approach as a versatile framework for accommodating varied dimensional changes, additionally; the paper introduces a novel partitioning strategy utilizing association rules algorithms, for optimized and scalable graph warehouse management.
Co-Authors Letrache, Khadija Ramdani, Mohammed