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Reseach Article

Infrequent Weighted Item Set Mining in Complex Data Analysis

by Sujatha Kamepalli, Raja Sekhara Rao Kurra, Sundara Krishna.y.k
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 103 - Number 5
Year of Publication: 2014
Authors: Sujatha Kamepalli, Raja Sekhara Rao Kurra, Sundara Krishna.y.k
10.5120/18070-9013

Sujatha Kamepalli, Raja Sekhara Rao Kurra, Sundara Krishna.y.k . Infrequent Weighted Item Set Mining in Complex Data Analysis. International Journal of Computer Applications. 103, 5 ( October 2014), 12-17. DOI=10.5120/18070-9013

@article{ 10.5120/18070-9013,
author = { Sujatha Kamepalli, Raja Sekhara Rao Kurra, Sundara Krishna.y.k },
title = { Infrequent Weighted Item Set Mining in Complex Data Analysis },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 103 },
number = { 5 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 12-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume103/number5/18070-9013/ },
doi = { 10.5120/18070-9013 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:33:44.318005+05:30
%A Sujatha Kamepalli
%A Raja Sekhara Rao Kurra
%A Sundara Krishna.y.k
%T Infrequent Weighted Item Set Mining in Complex Data Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 103
%N 5
%P 12-17
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Infrequent Weighted Association Mining (IWAM) is one of the main areas in data mining for extracting the rare items in high dimensional datasets. Traditional Association rule mining algorithms produce large number of candidate sets along with the database scans. Due to large number of transactions and database size, traditional methods consume more time to find the relevant association rules with the specified threshold. Prior and post database scans are required an additional effort to validate the association rules. Most of the existing weighted models are implemented for mining frequent itemsets, but finding infrequent itemset mining are useful in many recent fields like web,medical,cloud,complex databases,protein sequence etc. In weighted infrequent association rule mining, each item in the transaction is assigned a weight in order to mine high utility infrequent itemsets. In this proposed work, weighted association rule mining algorithm is proposed to find infrequent itemsets using weighted threshold measures. Proposed approach gives better results on real-time datasets compare to existing weighted models.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Weighted association rules Positive rule Measures Infrequent itemsets.