Association Rules with Opposite Items in Large Categorical Databases
Qiang Wei, Guoqing Chen · Flexible Query Answering Systems · 2001
Traditionally, the association rules discovered from categorical databases are like “Apples⇒Beers”, which means by default we focus on the attribute values which are equal to 1. Usually, we cannot deal with the association rules like “Age: 50–60 ∩ Female ⇒ ¬,Overdraw” whose semantics reflects “the Female users between 50 and 60 typically do not Overdraw ”. Here, we call this type of items (like “¬Overdraw”) as “opposite items”. In fact, however, in many categorical databases, “0” value does make sense. In this paper, we will propose a method to discover the association rules, which are composed of not only original items but also opposite items. Hereafter, Some optimizations are applied on the algorithm.