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...
We describe an efficient framework for Web personalization based on sequential and non-sequential pattern discovery from usage data. Our experimental results performed on real us...
Bamshad Mobasher, Honghua Dai, Tao Luo, Miki Nakag...
Data mining can extract important knowledge from large data collections - but sometimes these collections are split among various parties. Privacy concerns may prevent the parties...
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...
In this paper we consider concurrent execution of multiple data mining queries in the context of discovery of frequent itemsets. If such data mining queries operate on similar part...