A simple new algorithm is suggested for frequent itemset mining, using item probabilities as the basis for generating candidates. The method first finds all the frequent items, an...
The traditional association rule mining framework produces many redundant rules. The extent of redundancy is a lot larger than previously suspected. We present a new framework for...
We study the problem of finding frequent itemsets in a continuous stream of transactions. The current frequency of an itemset in a stream is defined as its maximal frequency ove...
This paper proposes a novel research dimension in the field of data mining, which is mining the future data before its arrival, or in other words: predicting association rules ahe...
Shenoda Guirguis, Khalil M. Ahmed, Nagwa M. El-Mak...
Mining frequent patterns in a data stream is very challenging for the high complexity of managing patterns with bounded memory against the unbounded data. While many approaches as...