A Divide and Conquer Approach for Deriving Partially Ordered Sub-structures-Reference-Cited by-同舟云学术

A Divide and Conquer Approach for Deriving Partially Ordered Sub-structures

Published:2005 Issue: Volume: Page:91-96
ISSN:0302-9743
Container-title:Advances in Knowledge Discovery and Data Mining
language:
Short-container-title:

Author:

Yahia S. Ben,Slimani Y.,Rezgui J.

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/11430919_12.pdf

Reference8 articles.

1. Pasquier, N., Bastide, Y., Taouil, R., Lakhal, L.: Efficient Mining of Association Rules Using Closed Itemset Lattices. Information Systems Journal 24, 25–46 (1999)

2. Han, J., Pei, J., Yin, Y.: Mining frequent patterns without candidate generation. In: Proceedings of the ACM-SIGMOD Intl. Conference on Management of Data (SIGMOD 2000), Dallas, Texas, pp. 1–12 (2000)

3. Cheung, W., Zaiane, O.: Incremental mining of frequent patterns without candidate generation or support constraint. In: Proceedings of the Seventh International Database Engineering and Applications Symposium (IDEAS 2003), Hong Kong, China (2003)

4. Grahne, G., Zhu, J.: Efficiently using prefix-trees in mining frequent itemsets. In: Goethals, B., Zaki, M.J. (eds.) Proceedings of Workshop on Frequent Itemset Mining Implementations (FIMI 2003), Florida, USA. IEEE, Los Alamitos (2003)

5. Stumme, G., Taouil, R., Bastide, Y., Pasquier, N., Lakhal, L.: Computing iceberg concept lattices with Titanic. J. on Knowledge and Data Engineering (KDE) 2, 189–222 (2002)

Cited by 1 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. Frequent closed itemset based algorithms;ACM SIGKDD Explorations Newsletter;2006-06