A novel method for mining association rules that are both quantitative and temporal using a multi-objective evolutionary algorithm is presented. This method successfully identifie...
With the rapid increase in the use of databases, the problem of missing values inevitably arises. The techniques developed to effectively recover these missing values should be hi...
Frequent itemset mining (FIM) is an essential part of association rules mining. Its application for other data mining tasks has also been recognized. It has been an active researc...
Two important constraints of association rule mining algorithm are support and confidence. However, such constraints-based algorithms generally produce a large number of redundant ...
Mining frequent closed itemsets provides complete and condensed information for non-redundant association rules generation. Extensive studies have been done on mining frequent clo...