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Maintenance of multi-level association rules discovery in dynamic database under a change of support threshold
Author(s)
Pumjun, Nophadon
Date Issued
January 13, 2016
Type
Conference Paper
Abstract
An association rule mining is often performed with a dynamic database and hierarchical items. The big problem of data mining process is a maintenance association rules while the database always changing. The purpose of this study is to extend the MLUp algorithm which can maintain a multilevel association rules discovery at the same minimum support threshold. In general, several mining tasks are required to deal with different support thresholds. MLUpCS can deal with a maintaining of mining multilevel association rules in dynamic databases under the different support threshold without re-mine a whole database. The result of MLUpCS algorithm experiment has shown how better performance than ML-T2 algorithm. The experimental results show the superior performance of MLUpCS when compared with ML-T2.
Citation
2015 12th International Conference on Fuzzy Systems and Knowledge Discovery Fskd 2015, 618-623, 2016