Abstract
ABSTRACT With the rise of new data generation processes and availability rates, new challenges appear linked with the information and pattern extraction for decisional processes. In these contexts, decision support systems (DSS) need to incrementally integrate the data flows to provide readable, understandable and meaningful conclusions. This research presents a novel adaptive DSS that offers updated and explainable knowledge for decision makers, especially in uncertain decision scenarios. Also, this work explores applications of this technology in some social fields, aiming to analyse the potential contribution of machine learning, combined with adaptive decision systems, in society.
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