A New Algorithm for Mining Frequent Itemsets Based on Fp-Search Algorithm with K Road Pruning

DOI

10.2991/cset-16.2016.24How to use a DOI?

Keywords

Association rule mining, Fp-search, FPNMP-search, MP-tree

Abstract

Association rule mining is an important approach in data mining. Based on analyzing many previous algorithms such as Apriori, Fp-growth, Eclat and Fp-search, we propose a new algorithm named FPNMP-search to mine frequent itemsets. With no need to construct the MP-tree, FPNMP-Search algorithm can effectively prune the redundant path and mine all frequent itemsets. The experimental results show that FPNMP-search is more efficient than Fp-growth and Fp-search.

Copyright

© 2016, 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  - Hao Jiang
AU  - Ruda Shen
PY  - 2016/08
DA  - 2016/08
TI  - A New Algorithm for Mining Frequent Itemsets Based on Fp-Search Algorithm with K Road Pruning
BT  - Proceedings of the 2016 International Conference on Computer Science and Electronic Technology
PB  - Atlantis Press
SP  - 98
EP  - 101
SN  - 2352-538X
UR  - https://doi.org/10.2991/cset-16.2016.24
DO  - 10.2991/cset-16.2016.24
ID  - Jiang2016/08
ER  -