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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 10, 2016.
Abstract: Data mining is the process of analyzing data so as to get useful information to be exploited by users. Association rules is one of data mining techniques used to detect different correlations and to reveal relationships among data individual items in huge data bases. These rules usually take the following form: if X then Y as independent attributes. An association rule has become a popular technique used in several vital fields of activity such as insurance, medicine, banks, supermarkets… Association rules are generated in huge numbers by algorithms known as Association Rules Mining algorithms. The generation of huge quantities of Association Rules may be time-and-effort consuming this is the reason behind an urgent necessity of an efficient and scaling approach to mine only the relevant and significant association rules. This paper proposes an innovative approach which mines the optimal rules from a large set of Association Rules in a distributive processing way to improve its efficiency and to decrease the running time.
Mouhir Mohammed, Balouki Youssef and Gadi Taoufiq, “Time-Saving Approach for Optimal Mining of Association Rules” International Journal of Advanced Computer Science and Applications(IJACSA), 7(10), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071031
@article{Mohammed2016,
title = {Time-Saving Approach for Optimal Mining of Association Rules},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.071031},
url = {http://dx.doi.org/10.14569/IJACSA.2016.071031},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {10},
author = {Mouhir Mohammed and Balouki Youssef and Gadi Taoufiq}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.