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.

R-Diffset vs. IR-Diffset: Comparison Analysis in Dense and Sparse Data

Author 1: Julaily Aida Jusoh
Author 2: Sharifah Zulaikha Tengku Hassan
Author 3: Wan Aezwani Wan Abu Bakar
Author 4: Syarilla Iryani Ahmad Saany
Author 5: Mohd Khalid Awang
Author 6: Norlina Udin @ Kamaruddin

Download PDF

Digital Object Identifier (DOI) : 10.14569/IJACSA.2023.0140241

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 2, 2023.

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

Abstract: The mining of concealed information from databases using Association Rule Mining seems to be promising. The successful extraction of this information will give a hand to many areas by aiding them in the process of finding solutions, economic projecting, commercialization policies, medical inspections, and numbers of other problems. ARM is the most outstanding method in the mining of remarkable related configurations from any groups of information. The important patterns encountered are categorized as recurrent/frequent and non-recurrent/infrequent. Most of the previous data mining methods concentrated on horizontal data set-ups. Nevertheless, recent studies have shown that vertical data formats are becoming the main concerns. One example of vertical data format is Rare Equivalence Class Transformation (R-Eclat). Due to its efficacy, R-Eclat algorithms have been commonly applied for the processing of large datasets. The R-Eclat algorithm is actually comprised of four types of variants. However, our work will only focus on the R-Diffset variant and Incremental R-Diffset (IR-Diffset). The performance analysis of the R-Diffset and IR-Diffset algorithms in the mining of sparse and dense data are compared. The processing time for R-Diffset algorithm, especially for sequential processing is very long. Thus, the incremental R-Diffset (IR-Diffset) has been established to solve this problem. While R-Diffset may only process the non-recurrent itemsets mining process in sequential form, IR-Diffset on the other hand has the capability to execute sequential data that have been fractionated. The advantages of this newly developed IR-Diffset may become a potential candidate in providing a time-efficient data mining process, especially those involving the large sets of data.

Keywords: R-Diffset; IR-Diffset; dense data; sparse data; comparison analysis

Julaily Aida Jusoh, Sharifah Zulaikha Tengku Hassan, Wan Aezwani Wan Abu Bakar, Syarilla Iryani Ahmad Saany, Mohd Khalid Awang and Norlina Udin @ Kamaruddin, “R-Diffset vs. IR-Diffset: Comparison Analysis in Dense and Sparse Data” International Journal of Advanced Computer Science and Applications(IJACSA), 14(2), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140241

@article{Jusoh2023,
title = {R-Diffset vs. IR-Diffset: Comparison Analysis in Dense and Sparse Data},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140241},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140241},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {2},
author = {Julaily Aida Jusoh and Sharifah Zulaikha Tengku Hassan and Wan Aezwani Wan Abu Bakar and Syarilla Iryani Ahmad Saany and Mohd Khalid Awang and Norlina Udin @ Kamaruddin}
}


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