Abstract :
We present, first, a hybrid-decision support system where a heuristic-data mining procedure is embedded to the original system. Using Peircean terminology, one of the main roles of this heuristic-data mining method is to evaluate n-ary predicates (i.e., quantitative variables, crisp or vague-fuzzy; and qualitative variables, precise or ambiguous) involved in the different types of decisions and meta-decisions presented in a decision-making process for a financial organization. After defining decisions from a logical-semiotic point of view, as a special type of inferential processes where meaning plays a fundamental role, examples of decisions (i.e., logical, emotional, and energetic or having the capacity for action), are discussed.
Keywords :
data mining; decision making; decision support systems; inference mechanisms; multi-agent systems; organisational aspects; Peircean terminology; decision-making; financial organization; heuristic-data mining; hybrid-decision support system; inferential process; logical-semiotic perspective; n-ary predicate evaluation; Decision making; Decision support systems; Electronic mail; Environmental economics; Modems; Power generation economics; Samarium; Terminology; Uncertainty; Utility theory;