Abstract
Developments in information and computing technologies have given rise to Intelligent Decision Support Systems (IDSS). The design of IDSS is largely based on data mining techniques and fuzzy logic. While decision-making is an advanced cognitive process, very little has been done in developing decision support methodologies that help integrate high level cognitive human reasoning and thinking elements within IDSS. This paper proposes a new IDSS methodology that incorporates both data mining techniques and human cognition in the process of decision-making. This proposed methodology involves a phased decision-support process. The initial phase focuses on phrasing a decision based on important criteria or conditions. The second phase involves the machine to analyse the required information from one or more large datasets. The third phase involves human cognition in making intelligent decisions based on key cognitive elements. Furthermore, the proposed methodology is tested on a large data set in the context of elderly care units in Melbourne.
Recommended Citation
Mekala, Sree Lekha; Mendoza, Antonette; and Bosua, Rachelle, "Towards a Synthesized Decision Support Methodology that Integrates Human Cognition and Data Mining" (2015). PACIS 2015 Proceedings. 208.
https://aisel.aisnet.org/pacis2015/208