The Research and Improvement Based on FP-Growth Data Mining Algorithm

DOI

10.2991/msota-16.2016.62How to use a DOI?

Keywords

FP-Growth algorithm; data mining, frequent itemsets; FP-tree, ENFP-growth algorithm

Abstract

In order to improve the availability in space domain and raise time efficiency of the algorithm, increasing more FP-array to decrease the traversing of FP-tree in this paper. It has put forward to applying the node switching strategy to generate more packed FP-tree. It has come up with increasing more FP-array to decrease the traversing of FP-tree. The space of storing FP-tree would be reduced, it could avoid allocating more other space and improve the utilization factor of the space. The solution indicates that the efficiency of time and space of improved FP-Growth algorithm is higher than that of classical FP-Growth algorithm and TFP-growth algorithm. What is new and original in this paper is it applies node switching strategy to generate more packed FP-tree and increasing more FP-array to decrease the traversing of FP-tree.

Copyright

© 2017, 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  - Quanzhu Yao
AU  - Xingxing Gao
AU  - Xueli Lei
AU  - Tong Zhang
PY  - 2016/12
DA  - 2016/12
TI  - The Research and Improvement Based on FP-Growth Data Mining Algorithm
BT  - Proceedings of 2016 International Conference on Modeling, Simulation and Optimization Technologies and Applications (MSOTA2016)
PB  - Atlantis Press
SP  - 287
EP  - 293
SN  - 2352-538X
UR  - https://doi.org/10.2991/msota-16.2016.62
DO  - 10.2991/msota-16.2016.62
ID  - Yao2016/12
ER  -