The traditional association rule mining framework produces many redundant rules. The extent of redundancy is a lot larger than previously suspected. We present a new framework for...
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...
Most association rule mining algorithms make use of discretization algorithms for handling continuous attributes. Discretization is a process of transforming a continuous attribute...
Karla Taboada, Eloy Gonzales, Kaoru Shimada, Shing...
This paper presents a hybrid, extensional and asymmetric matching approach designed to find out semantic relations (equivalence and subsumption) between entities issued from two ...
One of the important problems in data mining is discovering association rules from databases of transactions where each transaction consists of a set of items. The most time consu...