Proceedings of the 2015 International Conference on Computational Science and Engineering

Comparative study on the algorithm for mining association rules based on Data Mining

Authors
Jia Guo, Jing-yi Ren, Yu-jing Zhang
Corresponding Author
Jia Guo
Available Online July 2015.
DOI
10.2991/iccse-15.2015.9How to use a DOI?
Keywords
Data mining; Association rule; Algorithm; Frequent set
Abstract

This paper first introduces the classical algorithm -- Apriori algorithm of association rules in data mining. Then from several width, depth, partitioning, sampling, incremental updating and the angles of the association rules mining of classification discussion. Then using literature search and comparative analysis method to the common association rules mining algorithm are reviewed, mainly including FP-growth algorithm, DHP algorithm, Partition algorithm, FUP algorithm, CD algorithm. Development prospect of association rules mining is discussed.

Copyright
© 2015, 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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Volume Title
Proceedings of the 2015 International Conference on Computational Science and Engineering
Series
Advances in Computer Science Research
Publication Date
July 2015
ISBN
10.2991/iccse-15.2015.9
ISSN
2352-538X
DOI
10.2991/iccse-15.2015.9How to use a DOI?
Copyright
© 2015, 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/).

Cite this article

TY  - CONF
AU  - Jia Guo
AU  - Jing-yi Ren
AU  - Yu-jing Zhang
PY  - 2015/07
DA  - 2015/07
TI  - Comparative study on the algorithm for mining association rules based on Data Mining
BT  - Proceedings of the 2015 International Conference on Computational Science and Engineering
PB  - Atlantis Press
SP  - 44
EP  - 48
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccse-15.2015.9
DO  - 10.2991/iccse-15.2015.9
ID  - Guo2015/07
ER  -