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DFP-Growth: an efficient algorithm for mining frequent patterns in dynamic database

Abdullah, Zailani and Herawan, Tutut and Noraziah, A. and Mat Deris, Mustafa (2012) DFP-Growth: an efficient algorithm for mining frequent patterns in dynamic database. In: Proceedings of the Third international conference on Information Computing and Applications (ICICA'12), 14-16 September 2012, Chengde, China.

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Abstract

Mining frequent patterns in a large database is still an important and relevant topic in data mining. Nowadays, FP-Growth is one of the famous and benchmarked algorithms to mine the frequent patterns from FP-Tree data structure. However, the major drawback in FP-Growth is, the FP-Tree must be rebuilt all over again once the original database is changed. Therefore, in this paper we introduce an efficient algorithm called Dynamic Frequent Pattern Growth (DFP-Growth) to mine the frequent patterns from dynamic database. Experiments with three UCI datasets show that the DFP-Growth is up to 1.4 times faster than benchmarked FP-Growth, thus verify it efficiencies.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: dynamic database; efficient algorithm; frequent patterns
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: Normajihan Abd. Rahman
Date Deposited: 11 Apr 2013 06:33
Last Modified: 11 Apr 2013 06:33
URI: http://eprints.uthm.edu.my/id/eprint/3577
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