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An Efficient Approach for Mining Frequent Patterns Based on Traversing a Frequent Pattern Tree

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4 Author(s)
Show-Jane Yen ; Dept. of Comput. Sci. & Inf. Eng., Ming Chuan Univ. ; Yue-Shi Lee ; Chiu-Kuang Wang ; Jung-Wei Wu

Mining frequent patterns is an important task for knowledge discovery, which discovers the groups of items appearing always together excess of a user specified threshold. A famous algorithm for mining frequent patterns is FP-Growth which constructs a structure called FP-tree and recursively mines frequent patterns from this structure by building conditional FP-trees. However, It is costly to recursively construct conditional FP-trees. In order to decrease the usage of memory space and speed up the mining process, we propose an efficient approach for mining frequent patterns. Our approach only needs to construct a FP-tree and traverse each subtree of the FP-tree to generate all the frequent patterns for an item without constructing any other subtrees. Since there is no extra trees constructed and only a subtree needs to be traversed to generate frequent patterns for an item, our approach is much more efficient than FP-Growth algorithm. The experimental results also show that our approach significantly outperforms FP-Growth algorithm.

Published in:

Computer Science and Software Engineering, 2008 International Conference on  (Volume:4 )

Date of Conference:

12-14 Dec. 2008