An effective hash-based algorithm for mining association rules
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Beyond market baskets: generalizing association rules to correlations
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
The process of knowledge discovery in databases
Advances in knowledge discovery and data mining
Enhancements to the data mining process
Enhancements to the data mining process
Data Mining: An Overview from a Database Perspective
IEEE Transactions on Knowledge and Data Engineering
Mining for Strong Negative Associations in a Large Database of Customer Transactions
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Mining Association Rules with Negative Items Using Interest Measure
WAIM '00 Proceedings of the First International Conference on Web-Age Information Management
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Discovery of Multiple-Level Association Rules from Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Mining Generalized Association Rules
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
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In this paper, ARMiner, a data mining tools based on association rules, is introduced. Beginning with the system architecture, the characteristic and the function are displayed in details, including data transfer, concept hierarchy generalization, mining rules with negative items and the re-development of the system. We also show an example of the tool's application in this paper. Finally, some expectations for future work are presented.