The KDD process for extracting useful knowledge from volumes of data
Communications of the ACM
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
Fast discovery of association rules
Advances in knowledge discovery and data mining
Effective Data Mining Using Neural Networks
IEEE Transactions on Knowledge and Data Engineering
A data mining tool for producing characteristic classifications in the legal domain
DEXA '97 Proceedings of the 8th International Workshop on Database and Expert Systems Applications
An Efficient Data Mining Technique for Discovering Interesting Association Rules
DEXA '97 Proceedings of the 8th International Workshop on Database and Expert Systems Applications
XSearch: A Neural Network Based Tool for Components Search in a Distributed Object Environment
DEXA '01 Proceedings of the 12th International Conference on Database and Expert Systems Applications
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At the University of Linz a remarkable associative memory model has been developed. A neural network analogous self learning system with the capability of parallel and serial association. But, for data mining tasks it has one shortcoming. It can not reproduce how often it has seen a part of a pattern in its past - it is not able to compute frequencies. In this contribution we introduce an extension of the model with which frequencies, support and confidence are feasible. Besides, all advantages of the model could be retained. Short examples and a comparison with a common data mining tool complete the paper.