Discovery of inconsistent generalised coherent rules

Mining multiple-level association rules in a predefined taxonomy is an hierarchy that paves the way for generalised rule mining using interestingness measures like support and confidence. Coherent rule mining identifies significant rules in a database without using interestingness measures. In this paper, we propose a new mining algorithm called generalised inconsistent coherent rule mining (GICRM) for mining a new form of generalised coherent rules called inconsistent coherent rules. The discovered rules are called inconsistent because the correlation of the rules changes from one level of taxonomy to another. The rules are mined from a structured dataset of predefined taxonomy. The inconsistent rules mined would be noteworthy at the business point of view for taking strategic decisions in market basket analysis. © 2021 Inderscience Enterprises Ltd.