We present a framework for mining association rules from transactions consisting of categorical items where the data has been randomized to preserve privacy of individual transact...
Alexandre V. Evfimievski, Ramakrishnan Srikant, Ra...
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...
In this paper, a pattern-based stock data mining approach which transforms the numeric stock data to symbolic sequences, carries out sequential and non-sequential association analy...
We introduce a novel data mining technique for the analysis of gene expression. Gene expression is the effective production of the protein that a gene encodes. We focus on the cha...
Aleksandar Icev, Carolina Ruiz, Elizabeth F. Ryder
We address the problem of nding useful regions for two-dimensional association rules and decision trees. In a previous paper we presented ecient algorithms for computing optimiz...