Presenting association rules by hierarchy
关联规则的分层表达

Association rules are always presented as a list of rules with no further organization.Because many existing associations mining algorithms often produce a large number of rules,it is very difficult for the user to analyze them manually.In order to highlight the important rules and not suffer from being incomplete,a technique was proposed to intuitively present the discovered association rules in a hierarchical fashion.The discovered association rules were shown at different levels according rule's generality.The technique first found a subset of the association rules called the most-general rules set to give the user a general relationship or a big picture of the original rules set.Then,the user could selectively view more specific rules bellow the general rule that were interesting to him/her.Presented in such a way,rules could be easily comprehended by users.