Mining Closed Weighted Itemsets for Numerical Transaction Databases
In this article we extend the notion of closed itemsets of binary transaction databases to numerical transaction databases, and give an algorithm to mine them. We compare the computation time of our method and the case using scaling technique. We consider the case that information of closed itemsets of binarized database is given, and investigate how changes if algorithm utilize the information for mining by some experiments.
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- 1.Agrawal, R., Imielinski, T., Swami, A.: Mining association rules between sets of items in large databases. In: Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, pp. 207–216 (1993)Google Scholar
- 3.Ganter, B., Wille, R.: Applications of combinatorics and graph theory to the biological and social sciences. The IMA Volumes in Mathematics and Its Applications, vol. 17, pp. 139–167 (1989)Google Scholar
- 4.Kaytoue, M., Kuznetsov, S.O., Napoli, A.: Revisiting numerical patterns with formal concept analysis. In: Proceedings of the 22nd International Joint Conference on Artificial Intelligence, pp. 1342–1347 (2011)Google Scholar
- 5.Chan, R., Yang, Q., Shen, Y.-D.: Mining high utility itemsets. In: Proceedings of the Third International Conference on Data Mining, pp. 19–26 (2003)Google Scholar