An Improved Association Rule Algorithm Based on Indexed Array

DOI

10.2991/snce-18.2018.112How to use a DOI?

Keywords

Association rule; FMAIG; Index array

Abstract

Through analyzing the existing problems in the classical Apriori algorithm and FP growth algorithm, the author proposes a frequent itemsets mining algorithm based on indexed array in the paper. On the basis of Apriori algorithm, this algorithm not only narrows down the set of candidates effectively through introducing indexed array, but also saves memory with no need of using FP storage structure. By analyzing and comparing the experiment, we can reach a conclusion that the algorithm can effectively improve the efficiency of mining frequent itemsets.

Copyright

© 2018, 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  - Jianjing Mao
AU  - Xianjing Zhang
PY  - 2018/05
DA  - 2018/05
TI  - An Improved Association Rule Algorithm Based on Indexed Array
BT  - Proceedings of the 8th International Conference on Social Network, Communication and Education (SNCE 2018)
PB  - Atlantis Press
SP  - 554
EP  - 556
SN  - 2352-538X
UR  - https://doi.org/10.2991/snce-18.2018.112
DO  - 10.2991/snce-18.2018.112
ID  - Mao2018/05
ER  -