Data mining with time granules

Most of the existing studies only consider different item lifespans to find general temporal association rules, and this may neglect some useful information. In this paper, the concept of a hierarchy of time periods is considered and a new kind of rules, called hierarchical temporal rules, is proposed. The lifespan of an item in a time granule is calculated from its first appearance time to the end time in the time granule. The experimental results on a simulation dataset show the performance of the proposed algorithm under the new item lifespan.