A Synergy of Ontology and Knowledge Classification for Decision Support Systems

Abstract

Many problems within the software industry today emanate from the obliviousness that system development for decision support belongs to a category of problems that are classified complex or "wicked" in type. Therefore, procedural paradigms that address this phenomenon constitute areas of much exploration. Distinct with conventional problems, complex problems in information systems are problems that lack clarity in both their aims and solutions; lack definitive constructs and deficient of inherent logic that distinctively indicates when desired goals are achieved. This paper provides a discourse on the complex problems in Insurance Categorization. Ontology and knowledge classification in Insurance systems fall under this class of problems as insurance policies commonly describe problems exigent to unravel due to incomplete, contradictory and obstinately changing requirements. Because people exist in very unpredictable cultures with extensive categories of risk trajectories, it is commonly expected that individuals at some point in life are going to be challenged with situations which will hamper their privileges. Today, insurance businesses evolve either adversely or optimistically contingent upon the kinds of solutions they proffer for complex problems which may range from the competition, management and pecuniary situation. This paper decomposes key functionalities of complex insurance processes to model knowledge-based ontology adopting standard Enterprise Architecture archetypes that impress upon the intricacies of insurance information systems management. The relationships between classifications, perspectives and knowledge are examined to promote the organization of homogenous entities intended for grouping procedures for decision support systems. The strengths and constraints of imperative categorization approaches are described in terms of their ability to ruminate, discover, and apply contemporary expositions through modelling so as to harmonize business goals with application infrastructures.