An Intelligent Human-Computer Interaction System for Decision Support

This paper proposes a novel architecture for<br>developing decision support systems. Unlike conventional decision support systems, the proposed architecture endeavors to reveal the decision-making process such that humans' subjectivity can be<br>incorporated into a computerized system and, at the same time, to<br>preserve the capability of the computerized system in processing information objectively. A number of techniques used in developing the decision support system are elaborated to make the decisionmarking<br>process transparent. These include procedures for high dimensional data visualization, pattern classification, prediction, and evolutionary computational search. An artificial data set is first<br>employed to compare the proposed approach with other methods. A simulated handwritten data set and a real data set on liver disease diagnosis are then employed to evaluate the efficacy of the proposed<br>approach. The results are analyzed and discussed. The potentials of the proposed architecture as a useful decision support system are demonstrated.