Identification of pre-query fuzzy search rules and data mining techniques for integrated decision support frameworks

Information is more than a by-product of the daily operation of an enterprise. Information systems are now being utilized for transforming operational information into knowledge intended for decision making support. This new breed of information system is referred to as an analysis-based decision-oriented processing system. A recent literature survey concluded that companies desiring to successfully implement these new systems require an architected framework that incorporates analysis of decision scenarios in addition to establishing information requirements. This research focuses on the study of how decision scenarios can be enriched by incorporating appropriate information technology and artificial intelligence techniques within modern enterprises. An original architected decision support framework is proposed with the intention of complementing the Zachman Framework for information systems development. This research presents an original methodology for developing a priori selection rules for applying predefined and ad hoc queries to large datasets.