We address the issues of discovering significant binary relationships in transaction datasets in a weighted setting. Traditional model of association rule mining is adapted to han...
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...
Association rule mining is a key issue in data mining. However, the classical models ignore the difference between the transactions, and the weighted association rule mining does n...
Data mining has emerged to address the problem of transforming data into useful knowledge. Although most data mining techniques, such as Association Rules, substantially reduce th...
Abstract. Most research works about ontology or schema matching are based on symmetric similarity measures. By transposing the association rules paradigm, we propose to use asymmet...