This work proposes a theoretical guideline in the specific area of Frequent Itemset Mining (FIM). It supports the hypothesis that the use of neural network technology for the prob...
Mining of frequent closed itemsets has been shown to be more efficient than mining frequent itemsets for generating non-redundant association rules. The task is challenging in data...
The discovery of frequent patterns is a famous problem in data mining. While plenty of algorithms have been proposed during the last decade, only a few contributions have tried to ...
In this paper, we propose an efficient algorithm, called ICMiner (Inter-transaction Closed patterns Miner), for mining closed inter-transaction itemsets. Our proposed algorithm co...
Anthony J. T. Lee, Chun-sheng Wang, Wan-Yu Weng, Y...
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...