Proceedings of the 2016 International Conference on Computer Science and Electronic Technology

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

Authors
Hao Jiang, Ruda Shen
Corresponding Author
Hao Jiang
Available Online August 2016.
DOI
https://doi.org/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.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2016 International Conference on Computer Science and Electronic Technology
Part of series
Advances in Computer Science Research
Publication Date
August 2016
ISBN
978-94-6252-213-8
ISSN
2352-538X
DOI
https://doi.org/10.2991/cset-16.2016.24How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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  - 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  - https://doi.org/10.2991/cset-16.2016.24
ID  - Jiang2016/08
ER  -