Cubegrades: Generalizing Association Rules

摘要

Cubegrades are a generalization of association rules which represent how a set of measures (aggregates) is affected by modifying a cube through specialization (rolldown), generalization (rollup) and mutation (which is a change in one of the cube's dimensions). Cubegrades are significantly more expressive than association rules in capturing trends and patterns in data because they can use other standard aggregate measures, in addition to COUNT. Cubegrades are atoms which can support sophisticated “what if” analysis tasks dealing with behavior of arbitrary aggregates over different database segments. As such, cubegrades can be useful in marketing, sales analysis, and other typical data mining applications in business.