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A Novel Approach for Finding Frequent Itemsets done by Comparison based Technique

by Meghna Utmal, Shailendra Chourasia, Rashmi Vishwakarma
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 44 - Number 9
Year of Publication: 2012
Authors: Meghna Utmal, Shailendra Chourasia, Rashmi Vishwakarma
10.5120/6292-8488

Meghna Utmal, Shailendra Chourasia, Rashmi Vishwakarma . A Novel Approach for Finding Frequent Itemsets done by Comparison based Technique. International Journal of Computer Applications. 44, 9 ( April 2012), 23-27. DOI=10.5120/6292-8488

@article{ 10.5120/6292-8488,
author = { Meghna Utmal, Shailendra Chourasia, Rashmi Vishwakarma },
title = { A Novel Approach for Finding Frequent Itemsets done by Comparison based Technique },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 44 },
number = { 9 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 23-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume44/number9/6292-8488/ },
doi = { 10.5120/6292-8488 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:35:06.724103+05:30
%A Meghna Utmal
%A Shailendra Chourasia
%A Rashmi Vishwakarma
%T A Novel Approach for Finding Frequent Itemsets done by Comparison based Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 44
%N 9
%P 23-27
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Frequent pattern mining has been a focused theme in data mining research for over a decade. Abundant literature has been dedicated to this research and tremendous progress has been made, ranging from efficient and scalable algorithms for frequent itemset mining in transaction databases to numerous research frontiers, such as sequential pattern mining, structured pattern mining, correlation mining, associative classification, and frequent pattern-based clustering, as well as their broad applications. In this paper, we develop a new technique for more efficient pattern mining. Our method find frequent 1-itemset and then uses the heap tree sorting we are generating frequent patterns, so that many. We present efficient techniques to implement the new approach.

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Index Terms

Computer Science
Information Sciences

Keywords

Frequent Pattern Mining Maxheap Data Mining Data Structure

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