Discovery of Certain Association Rules from an Uncertain Database

Uncertainty is an intrinsic facet of human existence. The inherent significance of uncertainty is anything that cannot be allegedly declared with complete confidence. Some of the mathematical models that address uncertainty have already been employed and in use are Probability Theory, Fuzzy Theory, Rough Set, etc. The difference between the empirical and theoretical methods needs to be addressed to develop a business model that gives a panoptic study by analyzing various nuances of uncertainty. In recent years, research has shifted towards development of more sound business models using Data Mining to provide effective business understandings and strategies. As a consequence, uncertainty influence the measures used in Association Rules discovery and include some new interesting factors that may be lucrative for market-basket analysis. On handling uncertainty, rules that are formed become certain from uncertain ones that are found in database. The contextual meaning of the term vague association rules (VARs) used here is for the rules formed by the application of vague set theory rather than the vague nature of rules.