The problem of finding association rules in a large database of sales transactions has been widely studied in the literature, We discuss some of the weaknessesof the large itemset...
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...
In data mining applications, highly sized contexts are handled what usually results in a considerably large set of frequent itemsets, even for high values of the minimum support t...
Tarek Hamrouni, Sadok Ben Yahia, Engelbert Mephu N...
This paper presents new techniques for focusing the discoveryof frequent itemsets within large, dense datasets containing highly frequent items. The existence of highly frequent i...
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...