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A High Performance Algorithm for Mining Frequent Patterns: LPS-Miner

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4 Author(s)
Xiaoyun Chen ; Sch. of Inf. Sci. & Eng., Lanzhou Univ., Lanzhou ; Huiling Liu ; Pengfei Chen ; Longjie Li

In this paper, we present a novel frequent pattern mining algorithm, called LPS-Miner, which bases the pattern growth principle and uses two new data structures, LPS-FP-Tree (Light Partial-Support FP-Tree) and LPS-Forest (Light Partial-Support FP-Tree Forest) to present the database. LPS-FP-Tree is a variation of FP-Tree with lighter unidirectional nodes and the mining process depends on the partial-support of the patterns. LPS-Miner adopts partition and divide-and-conquer strategies in maximum, which decomposes the mining task into a set of smaller tasks. The light data structure and efficient memory management mechanism keep the memory usage stable and efficient. Other implementation-based optimizations, such as pruning and outputting-optimization, make the algorithm achieve high efficiency. We test our c++ implementation of this algorithm versus several other algorithms on four datasets. The experimental results show that our algorithm has better space and time efficiency.

Published in:

Information Science and Engineering, 2008. ISISE '08. International Symposium on  (Volume:2 )

Date of Conference:

20-22 Dec. 2008

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