Title :
Data mining with time granules
Author :
Tzung-Pei Hong ; Guo-Cheng Lan ; Pei-Shan Wu ; Shyue-liang Wang
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Univ. of Kaohsiung, Kaohsiung, Taiwan
Abstract :
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.
Keywords :
data mining; appearance time; data mining; end time; general temporal association rules; hierarchical temporal rules; item lifespans; time granules; time period hierarchy; Data mining; a hierarchy of time granules; association-rule mining; item lifespan; temporal association rules;
Conference_Titel :
Information Science and Service Science and Data Mining (ISSDM), 2012 6th International Conference on New Trends in
Conference_Location :
Taipei
Print_ISBN :
978-1-4673-0876-2
