The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Metadata Harvesting (OAI2)
  • Digital Archiving Policy
  • Promote your Publication

IJACSA

  • About the Journal
  • Call for Papers
  • Author Guidelines
  • Fees/ APC
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Guidelines
  • Fees
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Subscribe

Article Details

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.

Time-Saving Approach for Optimal Mining of Association Rules

Author 1: Mouhir Mohammed
Author 2: Balouki Youssef
Author 3: Gadi Taoufiq

Download PDF

Digital Object Identifier (DOI) : 10.14569/IJACSA.2016.071031

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 10, 2016.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

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.

Keywords: MDPREF Algorithm; Association Rules mining; Data partitioning; Optimization (profitability, efficiency and Risks) ; Bagging

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}
}


IJACSA

Upcoming Conferences

Future of Information and Communication Conference (FICC) 2023

2-3 March 2023

  • Virtual

Computing Conference 2023

22-23 June 2023

  • London, United Kingdom

IntelliSys 2023

7-8 September 2023

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 2023

2-3 November 2023

  • San Francisco, United States
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. Registered in England and Wales. Company Number 8933205. All rights reserved. thesai.org