An Associative Memory for Association Rule Mining

— Association Rule Mining is a thoroughly studied problem in Data Mining. Its solution has been aimed for by approaches based on different strategies involving, for instance, the use of novel data structures to represent the knowledge discovered, the transformation of the input data to speed up the process, the exploitation of the itemset properties either to traverse the possible itemset search space optimally or to form compact representation of the frequent itemsets employed for the generation of the corresponding final rules, and others. Surprisingly, biologically-inspired approaches have rarely been proposed. On the other hand, Artificial Neural Networks have been already proposed and satisfactorily used in some data-mining problems. For instance, in tasks of classification, clustering and prediction; however, their suitability for association rule mining is still uncertain. In this work, we focus on investigating if a type of mapping neural network, better known as an associ...

• Type: Conference
• Year: 2007
• Where: IJCNN
• Authors: Vicente O. Baez-Monroy, Simon O'Keefe
• Keywords: Association Rule Mining, Associative Memory, IJCNN 2007, Neural Network