A New Algorithm for Mining Frequent Itemsets Based on Fp-Search Algorithm with K Road Pruning
Hao Jiang, Ruda Shen
Available Online August 2016.
- https://doi.org/10.2991/cset-16.2016.24How to use a DOI?
- Association rule mining, Fp-search, FPNMP-search, MP-tree
- 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.
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 -