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Frequent item sets mining plays an important role in association rules mining. A variety of algorithms for finding frequent item sets in very large transaction databases have been developed. Although many techniques were proposed for maintenance of the discovered rules when new transactions are added, little work is done for maintaining the discoveredrules when some transactions are deleted from the database. Updates are fundamental aspect of data management. In this paper, a decremental association rules mining algorithm is present for updating the discovered association rules when some transactions are removed from the original data set. Extensive experiments were conducted to evaluate theperformance of the proposed algorithm. The results show that the proposed algorithm is efficient and outperforms other well-known algorithms.


Decremental Mining, Association Rules Maintenance, Updating Association Rules

Cite this paper

M. Taha, T. Gharib and H. Nassar -DARM: Decremental Association Rules Mining,- Journal of Intelligent Learning Systems and Applications, Vol. 3 No. 3, 2011, pp. 181-189. doi: 10.4236-jilsa.2011.33019.

Autor: Mohamed Taha, Tarek F. Gharib, Hamed Nassar

Fuente: http://www.scirp.org/


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