Deciding Entailment of Implications with Support and Confidence in   Polynomial Space
  Association Rules are a basic concept of data mining. They are, however, not understood as logical objects which can be used for reasoning. The purpose of this paper is to investigate a model based semantic for implications with certain constraints on their support and confidence in relational data, which then resemble association rules, and to present a possibility to decide entailment for them. 
Daniel Borchmann
cs.LO