We propose a framework, called MIC, which adopts an information-theoretic approach to address the problem of quantitative association rule mining. In our MIC framework, we first d...
In the paper a new data mining algorithm for finding the most interesting dependence rules is described. Dependence rules are derived from the itemsets with support significantly ...
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...
Given a donor database by a charitable organization in Hong Kong, we propose to use a new data mining technique to discover fuzzy rules for direct marketing. The discovered fuzzy ...
This paper introduces a new approach to a problem of data sharing among multiple parties, without disclosing the data between the parties. Our focus is data sharing among two parti...