During the requirements analysis phase, which guides the Business Intelligence project success, several problems can be encountered: poor information collection, incomplete, uncertain or imprecise data. These difficulties can negatively influence the analyzing decision-making requirements process and, therefore, collective requirements are often vague and not measurable. However, several methods are proposed in the literature to estimate incomplete or missing facts. These methods do not take into account the incomplete needs case, especially in the decision-making system case. This article does not present a rigorous study but rather an incompleteness overview and highlights the research openings concerning this research area. We can conclude that despite the use of artificial intelligence techniques, evaluation studies of missing quantitative data are not significant, while the case of missing decision needs evaluation is not treated at all.
Volume 12 | 07-Special Issue
Pages: 1648-1652
DOI: 10.5373/JARDCS/V12SP7/20202270