Title :
Time Series Data Mining Method Based on Lightly-Supported Boolean Association Rules
Author :
Zhang, Zhonglin ; Chen, Zhi
Author_Institution :
Lanzhou Jiaotong Univ., Lanzhou
Abstract :
The mining of association rules mainly aims at the strong association rules, but lacks of efficient methods to mine the rules within the item sets that occur not much frequently. With the separation of the items by their time property, this paper discusses a new method of mining the lightly-supported Boolean association rules.
Keywords :
Boolean functions; data mining; time series; item sets; lightly-supported Boolean association rules; time series data mining; Association rules; Data engineering; Data mining; Electronic mail; Frequency; Pattern analysis; Stochastic processes;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2874-8
DOI :
10.1109/FSKD.2007.589
