Design and Implementation of Improved Algorithm for Association Rules Mining

DOI

10.2991/iccsee.2013.79How to use a DOI?

Keywords

association rules, data mining, frequent item sets, algorithm, exception rules,

Abstract

For traditional algorithm of association rules mining based on frequent item sets and ignored the exception rules, as well as the traditional issues such as frequent item sets algorithm can be costly, a new association rules mining algorithm which isn’t based on frequent item sets is given in this paper. This method scanned the database once firstly, and then uses the logical and set theory operations to generate association rules, including frequent association rules and exception rules. Through case analysis, results showed that the algorithm with high accuracy, low cost, and the ability to generate exception rules could provide some reference data for exception knowledge mining.

Copyright

© 2013, 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  - Lin Zhang
AU  - Jian-li Zhhang
PY  - 2013/03
DA  - 2013/03
TI  - Design and Implementation of Improved Algorithm for Association Rules Mining
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 308
EP  - 311
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.79
DO  - 10.2991/iccsee.2013.79
ID  - Zhang2013/03
ER  -