Time Series Data Mining Method Based on Lightly-Supported Boolean Association Rules

Authors:
Zhonglin Zhang;Zhi Chen
Affiliations:
Lanzhou Jiaotong University, Lanzhou;Lanzhou Jiaotong University, Lanzhou
Venue:
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01
Year:
2007

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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.