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Reseach Article

A Collaborative Approach of Frequent Item Set Mining: A Survey

by Arpan Shah, Pratik Patel
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 107 - Number 8
Year of Publication: 2014
Authors: Arpan Shah, Pratik Patel
10.5120/18775-0088

Arpan Shah, Pratik Patel . A Collaborative Approach of Frequent Item Set Mining: A Survey. International Journal of Computer Applications. 107, 8 ( December 2014), 34-36. DOI=10.5120/18775-0088

@article{ 10.5120/18775-0088,
author = { Arpan Shah, Pratik Patel },
title = { A Collaborative Approach of Frequent Item Set Mining: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { December 2014 },
volume = { 107 },
number = { 8 },
month = { December },
year = { 2014 },
issn = { 0975-8887 },
pages = { 34-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume107/number8/18775-0088/ },
doi = { 10.5120/18775-0088 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:40:34.169896+05:30
%A Arpan Shah
%A Pratik Patel
%T A Collaborative Approach of Frequent Item Set Mining: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 107
%N 8
%P 34-36
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data mining defines hidden pattern in data sets and association between the patterns. In data mining, association rule mining is key technique for discovering useful patterns from large collection of data. Frequent iemset mining is a step of association rule mining. Frequent itemset mining is used to gather itemsets after discovering association rules. In this paper, we have explained fundamentals of frequent itemset mining. We have defined present's techniques for frequent item set mining. From the large variety of capable algorithms that have been established we will compare the most important ones. We will organize the algorithms and investigate their run time performance.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Association rules Data mining Frequent Item set Mining FP growth Minimum Support