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...
This paper proposes a fault-prone module prediction method that combines association rule mining with logistic regression analysis. In the proposed method, we focus on three key m...
While traditional algorithms concern positive associations between binary or quantitative attributes of databases, this paper focuses on mining both positive and negative fuzzy ass...
Peng Yan, Guoqing Chen, Chris Cornelis, Martine De...
This paper presents a hybrid, extensional and asymmetric matching approach designed to find out semantic relations (equivalence and subsumption) between entities issued from two ...
Popular data mining methods support knowledge discovery from patterns that hold in binary relations. We study the generalization of association rule mining within arbitrary n-ary ...