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DOI: 10.14569/IJACSA.2013.040326
PDF

A New Viewpoint for Mining Frequent Patterns

Author 1: Thanh-Trung Nguyen
Author 2: Phi-Khu Nguyen

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 4 Issue 3, 2013.

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

Abstract: According to the traditional viewpoint of Data mining, transactions are accumulated over a long period of time (in years) in order to find out the frequent patterns associated with a given threshold of support, and then they are applied to practice of business as important experience for the next business processes. From the point of view, many algorithms have been proposed to exploit frequent patterns. However, the huge number of transactions accumulated for a long time and having to handle all the transactions at once are still challenges for the existing algorithms. In addition, today, new characteristics of the business market and the regular changes of business database with too large frequency of added-deleted-altered operations are demanding a new algorithm mining frequent patterns to meet the above challenges. This article proposes a new perspective in the field of mining frequent patterns: accumulating frequent patterns along with a mathematical model and algorithms to solve existing challenges.

Keywords: accumulating frequent patterns; data mining; frequent pattern; horizontal parallelization; representative set; vertical parallelization

Thanh-Trung Nguyen and Phi-Khu Nguyen, “A New Viewpoint for Mining Frequent Patterns” International Journal of Advanced Computer Science and Applications(IJACSA), 4(3), 2013. http://dx.doi.org/10.14569/IJACSA.2013.040326

@article{Nguyen2013,
title = {A New Viewpoint for Mining Frequent Patterns},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2013.040326},
url = {http://dx.doi.org/10.14569/IJACSA.2013.040326},
year = {2013},
publisher = {The Science and Information Organization},
volume = {4},
number = {3},
author = {Thanh-Trung Nguyen and Phi-Khu Nguyen}
}



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.

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