Association Rules Mining (ARM) algorithms are designed to find sets of frequently occurring items in large databases. ARM applications have found their way into a variety of field...
In recent years interest has grown in “mining” large databases to extract novel and interesting information. Knowledge Discovery in Databases (KDD) has been recognised as an em...
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...
We present two algorithms for learning large-scale gene regulatory networks from microarray data: a modified informationtheory-based Bayesian network algorithm and a modified asso...
Zan Huang, Jiexun Li, Hua Su, George S. Watts, Hsi...
We present a system towards the integration of data mining into relational databases. To this end, a relational database model is proposed, based on the so called virtual mining vi...