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Reseach Article

A Performance based Transaction Reduction Algorithm for Discovering Frequent Patterns

by V. Vijayalakshmi, A. Pethalakshmi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 98 - Number 4
Year of Publication: 2014
Authors: V. Vijayalakshmi, A. Pethalakshmi
10.5120/17170-7242

V. Vijayalakshmi, A. Pethalakshmi . A Performance based Transaction Reduction Algorithm for Discovering Frequent Patterns. International Journal of Computer Applications. 98, 4 ( July 2014), 18-21. DOI=10.5120/17170-7242

@article{ 10.5120/17170-7242,
author = { V. Vijayalakshmi, A. Pethalakshmi },
title = { A Performance based Transaction Reduction Algorithm for Discovering Frequent Patterns },
journal = { International Journal of Computer Applications },
issue_date = { July 2014 },
volume = { 98 },
number = { 4 },
month = { July },
year = { 2014 },
issn = { 0975-8887 },
pages = { 18-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume98/number4/17170-7242/ },
doi = { 10.5120/17170-7242 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:25:51.194344+05:30
%A V. Vijayalakshmi
%A A. Pethalakshmi
%T A Performance based Transaction Reduction Algorithm for Discovering Frequent Patterns
%J International Journal of Computer Applications
%@ 0975-8887
%V 98
%N 4
%P 18-21
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Association rules are the main technique to determine the frequent item set in data mining. When a large number of item sets are processed by the database, it needs to be scanned multiple times. Consecutively, multiple scanning of the database increases the number of rules generation, which then consume more system resources. Existing approach TR-BAM scans the unnecessary transaction which takes more time to find frequent item set. This paper presents a modified transaction reduction technique named PBTRA which reduces the scanning times by cutting down the unnecessary transaction row. So, the corresponding item set is extracted directly without moving for entire database. Moreover, it exploits horizontal transaction of the matrix that automatically reduces the entire database scanning. Experimental results validate the performance of the proposed approach and expose that proposed method is more effective and efficient than previously proposed algorithm.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Frequent Item Set Apriori Support Count. TR-BAM PBTRA