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
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Online Access:http://irep.iium.edu.my/79195/1/79195_Improved%20BVBUC%20Algorithm%20to%20Discover.pdf
http://irep.iium.edu.my/79195/
https://doi.org/10.4028/www.scientific.net/AMM.892.157
https://doi.org/10.4028/www.scientific.net/AMM.892.157
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Institution: Universiti Islam Antarabangsa Malaysia
Language: English
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spelling my.iium.irep.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
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
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/79195/1/79195_Improved%20BVBUC%20Algorithm%20to%20Discover.pdf
http://irep.iium.edu.my/79195/
https://doi.org/10.4028/www.scientific.net/AMM.892.157
https://doi.org/10.4028/www.scientific.net/AMM.892.157
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