SeqARM: An Association Rule Mining Algorithm Based on Sequence Constraint

DOI

10.2991/citcs.2012.204How to use a DOI?

Keywords

association rule; sequence constraint; SeqARM; FITree

Abstract

Sequence constraint mainly considers the occurrence time of item, which can determine whether an association rule is valid. This paper proposes a novel algorithm SeqARM that aims to mine strong association rule with sequence constraint and runs on the second phase of association rule mining. SeqARM employs a fine data structure, named FI-Tree, which is used to save and find frequent itemsets according to a few characteristics of association rule. This work can dramatically reduce the number of invalid association rules, and speed up the procedure of association rules. At last, the experiments prove that SeqARM can improve the performance and effect of the association rule mining.

Copyright

© 2012, 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  - Shenshen Bai
PY  - 2012/11
DA  - 2012/11
TI  - SeqARM: An Association Rule Mining Algorithm Based on Sequence Constraint
BT  - Proceedings of the 2012 National Conference on Information Technology and Computer Science
PB  - Atlantis Press
SP  - 804
EP  - 807
SN  - 1951-6851
UR  - https://doi.org/10.2991/citcs.2012.204
DO  - 10.2991/citcs.2012.204
ID  - Bai2012/11
ER  -