Improved BVBUC algorithm to discover closed itemsets in long biological datasets

The task in mining closed frequent itemsets requires the algorithm to mine the frequent ones then determine its closure. The efficiency of closure computation is very important as it will determine the total mining time and the required memory. Over the years, many closure computation methods have b...

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Main Authors:	Md Zaki, Fatimah Audah, Zulkurnain, Nurul Fariza
Format:	Article
Language:	English
Published:	Trans Tech Publications Ltd, Switzerland 2019
Subjects:	QA76 Computer software
Online Access:	http://irep.iium.edu.my/79195/ http://irep.iium.edu.my/79195/ http://irep.iium.edu.my/79195/ http://irep.iium.edu.my/79195/1/79195_Improved%20BVBUC%20Algorithm%20to%20Discover.pdf

id	iium-79195
recordtype	eprints
spelling	iium-791952020-03-10T08:56:56Z http://irep.iium.edu.my/79195/ Improved BVBUC algorithm to discover closed itemsets in long biological datasets Md Zaki, Fatimah Audah Zulkurnain, Nurul Fariza QA76 Computer software The task in mining closed frequent itemsets requires the algorithm to mine the frequent ones then determine its closure. The efficiency of closure computation is very important as it will determine the total mining time and the required memory. Over the years, many closure computation methods have been proposed to achieve these goals. However, to the best of our knowledge, there is no suitable method that can be adapted for algorithms that enumerate the rowset lattice, which is effective for biological datasets. Therefore, this paper proposed a method for computing closure compare with the method used in BVBUC algorithm method. Finally, BVBUC_I is proposed and the performances of these algorithms were evaluated using two synthetic datasets and three real datasets. The results of these tests proved the efficiency of the proposed method. Trans Tech Publications Ltd, Switzerland 2019-06 Article PeerReviewed application/pdf en http://irep.iium.edu.my/79195/1/79195_Improved%20BVBUC%20Algorithm%20to%20Discover.pdf Md Zaki, Fatimah Audah and Zulkurnain, Nurul Fariza (2019) Improved BVBUC algorithm to discover closed itemsets in long biological datasets. Applied Mechanics and Materials, 892. pp. 157-167. ISSN 1662-7482 https://doi.org/10.4028/www.scientific.net/AMM.892.157 https://doi.org/10.4028/www.scientific.net/AMM.892.157
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Md Zaki, Fatimah Audah Zulkurnain, Nurul Fariza Improved BVBUC algorithm to discover closed itemsets in long biological datasets
description	The task in mining closed frequent itemsets requires the algorithm to mine the frequent ones then determine its closure. The efficiency of closure computation is very important as it will determine the total mining time and the required memory. Over the years, many closure computation methods have been proposed to achieve these goals. However, to the best of our knowledge, there is no suitable method that can be adapted for algorithms that enumerate the rowset lattice, which is effective for biological datasets. Therefore, this paper proposed a method for computing closure compare with the method used in BVBUC algorithm method. Finally, BVBUC_I is proposed and the performances of these algorithms were evaluated using two synthetic datasets and three real datasets. The results of these tests proved the efficiency of the proposed method.
format	Article
author	Md Zaki, Fatimah Audah Zulkurnain, Nurul Fariza
author_facet	Md Zaki, Fatimah Audah Zulkurnain, Nurul Fariza
author_sort	Md Zaki, Fatimah Audah
title	Improved BVBUC algorithm to discover closed itemsets in long biological datasets
title_short	Improved BVBUC algorithm to discover closed itemsets in long biological datasets
title_full	Improved BVBUC algorithm to discover closed itemsets in long biological datasets
title_fullStr	Improved BVBUC algorithm to discover closed itemsets in long biological datasets
title_full_unstemmed	Improved BVBUC algorithm to discover closed itemsets in long biological datasets
title_sort	improved bvbuc algorithm to discover closed itemsets in long biological datasets
publisher	Trans Tech Publications Ltd, Switzerland
publishDate	2019
url	http://irep.iium.edu.my/79195/ http://irep.iium.edu.my/79195/ http://irep.iium.edu.my/79195/ http://irep.iium.edu.my/79195/1/79195_Improved%20BVBUC%20Algorithm%20to%20Discover.pdf
first_indexed	2023-09-18T21:51:20Z
last_indexed	2023-09-18T21:51:20Z
_version_	1777413788894494720

Improved BVBUC algorithm to discover closed itemsets in long biological datasets

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