|Table of Contents|

[1] Yang Ming, Yang Ping, Ji Genlin, et al. Fast FP-Growth for association rule mining [J]. Journal of Southeast University (English Edition), 2003, 19 (4): 320-323. [doi:10.3969/j.issn.1003-7985.2003.04.004]
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Fast FP-Growth for association rule mining()
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
19
Issue:
2003 4
Page:
320-323
Research Field:
Computer Science and Engineering
Publishing date:
2003-12-30

Info

Title:
Fast FP-Growth for association rule mining
Author(s):
Yang Ming1;  2;  Yang Ping3;  Ji Genlin2;  Sun Zhihui2
1Department of Computer Science and Engineering, Auhui University of Technology and Science, Wuhu 241000, China
2Department of Computer Science and Engineering, Southeast University, Nanjing 210096, China
3Departme
Keywords:
data mining;  frequent itemsets;  association rules;  frequent pattern tree(FP-tree)
PACS:
TP311
DOI:
10.3969/j.issn.1003-7985.2003.04.004
Abstract:
In this paper, we propose an efficient algorithm, called FFP-Growth(short for fast FP-Growth), to mine frequent itemsets. Similar to FP-Growth, FFP-Growth searches the FP-tree in the bottom-up order, but need not construct conditional pattern bases and sub-FP-trees, thus, saving a substantial amount of time and space, and the FP-tree created by it is much smaller than that created by TD-FP-Growth, hence improving efficiency. At the same time, FFP-Growth can be easily extended for reducing the search space as TD-FP-Growth(M)and TD-FP-Growth(C). Experimental results show that the algorithm of this paper is effective and efficient.

References:

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Memo

Memo:
Biography: Yang Ming(1964—), male, graduate, professor, yangming@seu.edu.cn.
Last Update: 2003-12-20