The Augmented Itemset Tree: A Data Structure for Online Maximum Frequent Pattern Mining

Author:

Schmidt Jana,Kramer Stefan

Publisher

Springer Berlin Heidelberg

Reference20 articles.

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3. Cheung, D.W., Han, J., Ng, V.T., Wong, C.Y.: Maintenance of discovered association rules in large databases: An incremental updating technique. In: Proceedings of the Twelfth International Conference on Data Engineering (ICDE), pp. 106–114. IEEE Computer Society, Los Alamitos (1996)

4. Cheung, W., Zaiane, O.R.: Incremental mining of frequent patterns without candidate generation or support. In: IDEAS 2003: Proceedings of the 7th International Database Engineering and Applications Symposium 2003, pp. 111–116. IEEE Computer Society, Los Alamitos (2003)

5. Chi, Y., Wang, H., Yu, P.S., Muntz, R.R.: Moment: Maintaining closed frequent itemsets over a stream sliding window. In: Proceedings of the Fourth IEEE International Conference on Data Mining, pp. 59–66. IEEE Computer Society, Los Alamitos (2004)

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Online Induction of Probabilistic Real-Time Automata;Journal of Computer Science and Technology;2014-05

2. Online Induction of Probabilistic Real Time Automata;2012 IEEE 12th International Conference on Data Mining;2012-12

3. The Augmented Itemset Tree: A Data Structure for Online Maximum Frequent Pattern Mining;Discovery Science;2011

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