We present an algorithm for mining association rules from relational tables containing numeric and categorical attributes. The approach is to merge adjacent intervals of numeric v...
The output of boolean association rule mining algorithms is often too large for manual examination. For dense datasets, it is often impractical to even generate all frequent items...
Microarray datasets typically contain large number of columns but small number of rows. Association rules have been proved to be useful in analyzing such datasets. However, most e...
Gao Cong, Anthony K. H. Tung, Xin Xu, Feng Pan, Ji...
We study the problem of discovering association rules that display regular cyclic variation over time. For example, if we compute association rules over monthly sales data, we may...
Associative classification is a novel and powerful method originating from association rule mining. In the previous studies, a relatively small number of high-quality association...