Comparative Study of Various Improved Versions of Apriori Algorithm

Journal Title: INTERNATIONAL JOURNAL OF ENGINEERING TRENDS AND TECHNOLOGY - Year 2013, Vol 4, Issue 4

Abstract

 — In Data Mining Research, Frequent Item set Mining has been considered an important task. These item sets leads to the generation of Association rules. These rules tell about the presence of one item with respect to the presence of another item in large dataset. There are efficient methods for generating Association Rules from large databases. This paper describes methods for frequent item set mining and various improvements in the classical algorithm “Apriori” for frequent item set generation.

Authors and Affiliations

Shruti Aggarwal#1 , Ranveer Kaur

Keywords

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  • EP ID EP130606
  • DOI -
  • Views 115
  • Downloads 0

How To Cite

Shruti Aggarwal#1, Ranveer Kaur (2013).  Comparative Study of Various Improved Versions of Apriori Algorithm. INTERNATIONAL JOURNAL OF ENGINEERING TRENDS AND TECHNOLOGY, 4(4), 687-690. https://europub.co.uk/articles/-A-130606