Mining hierarchical temporal association rules in a publication database

Abstract

Different from the existing studies, this work presents a new kind of rules with the concept of a hierarchy of time granules, namely hierarchical temporal association rules. The lifespan of an item in a time granule is calculated from the publication time of the item to the end time in the time granule. A three-phase mining framework is proposed to effectively and efficiently find this kind of rules from a temporal database. The experimental results show the performance of the proposed algorithm under the item lifespan definition.