Towards an Agent-Based Approach for Multidimensional Analyses of Semantic Web Data

Abstract : OLAP analytical systems are essential technologies in decision-making processes; they provide an efficient way to carry out complex analysis in a simpler and faster way to decision-makers. In today’s dynamic and competitive business contexts, the stored internal data within companies does no longer provide enough information for decision-making processes. Therefore, decision analysis systems could be improved by including external data available through the semantic web in order to provide multiple perspectives to decision makers. In this article, we describe a preliminary approach based on the use of multi-agent systems for multidimensional analysis of external data coming from the semantic web also gives a short review of recent research works combining business intelligence and semantic web technologies. The proposed approach is based on an evolutionary architecture by dint of the “agents” technology. The different stages of the analysis are considered tasks that will be assimilated to services, managed by agents.

Keywords : OLAP; semantic web; business intelligence; multi-agent system; multidimensional analysis.

Recommended citation: El Hajjami, S., Berrada, M., Harti, M., & Diallo, G. (2017, April). Towards an agent-based approach for multidimensional analyses of semantic web data. In 2017 Intelligent Systems and Computer Vision (ISCV) (pp. 1-6). IEEE.