Improved algorithm for mining maximum frequent patterns based on FP-Tree

DOI

10.2991/iccia.2012.202How to use a DOI?

Keywords

data mining,association rule,maximum frequent pattern,FP-Tree

Abstract

Mining association rule is an important matter in data mining, in which mining maximum frequent patterns is a key problem. Many of the previous algorithms mine maximum frequent patterns by producing candidate patterns firstly, then pruning. But the cost of producing candidate patterns is very high, especially when there exists long patterns. In this paper, the structure of a FP-tree is improved, we propose a fast algorithm based on FP-Tree for mining maximum frequent patterns, the algorithm does not produce maximum frequent candidate patterns and is more effectively than other improved algorithms. The new FP-Tree is a one-way tree and only retains pointers to point its father in each node, so at least one third of memory is saved. Experiment results show that the algorithm is efficient and saves memory space.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Naili Liu
AU  - Lei Ma
PY  - 2014/05
DA  - 2014/05
TI  - Improved algorithm for mining maximum frequent patterns based on FP-Tree
BT  - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
PB  - Atlantis Press
SP  - 833
EP  - 836
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccia.2012.202
DO  - 10.2991/iccia.2012.202
ID  - Liu2014/05
ER  -