An improved association rule mining algorithm for large data

The data with the advancement of information technology are increasing on daily basis. The data mining technique has been applied to various fields. The complexity and execution time are the major factors viewed in existing data mining techniques. With the rapid development of database technology, m...

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Autores principales:	Zhao Zhenyi, Jian Zhou, Gaba Gurjot Singh, Alroobaea Roobaea, Masud Mehedi, Rubaiee Saeed
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2021
Materias:	rule mining apriori algorithm frequent item sets r-tree algorithm dynamic algorithm precision ratio accuracy Science Q Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/f1baa2b003d14ef78577a93207b8a422
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:f1baa2b003d14ef78577a93207b8a422
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spelling	oai:doaj.org-article:f1baa2b003d14ef78577a93207b8a4222021-12-05T14:10:51ZAn improved association rule mining algorithm for large data2191-026X10.1515/jisys-2020-0121https://doaj.org/article/f1baa2b003d14ef78577a93207b8a4222021-06-01T00:00:00Zhttps://doi.org/10.1515/jisys-2020-0121https://doaj.org/toc/2191-026XThe data with the advancement of information technology are increasing on daily basis. The data mining technique has been applied to various fields. The complexity and execution time are the major factors viewed in existing data mining techniques. With the rapid development of database technology, many data storage increases, and data mining technology has become more and more important and expanded to various fields in recent years. Association rule mining is the most active research technique of data mining. Data mining technology is used for potentially useful information extraction and knowledge from big data sets. The results demonstrate that the precision ratio of the presented technique is high comparable to other existing techniques with the same recall rate, i.e., the R-tree algorithm. The proposed technique by the mining effectively controls the noise data, and the precision rate is also kept very high, which indicates the highest accuracy of the technique. This article makes a systematic and detailed analysis of data mining technology by using the Apriori algorithm.Zhao ZhenyiJian ZhouGaba Gurjot SinghAlroobaea RoobaeaMasud MehediRubaiee SaeedDe Gruyterarticlerule miningapriori algorithmfrequent item setsr-tree algorithmdynamic algorithmprecision ratioaccuracyScienceQElectronic computers. Computer scienceQA75.5-76.95ENJournal of Intelligent Systems, Vol 30, Iss 1, Pp 750-762 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	rule mining apriori algorithm frequent item sets r-tree algorithm dynamic algorithm precision ratio accuracy Science Q Electronic computers. Computer science QA75.5-76.95
spellingShingle	rule mining apriori algorithm frequent item sets r-tree algorithm dynamic algorithm precision ratio accuracy Science Q Electronic computers. Computer science QA75.5-76.95 Zhao Zhenyi Jian Zhou Gaba Gurjot Singh Alroobaea Roobaea Masud Mehedi Rubaiee Saeed An improved association rule mining algorithm for large data
description	The data with the advancement of information technology are increasing on daily basis. The data mining technique has been applied to various fields. The complexity and execution time are the major factors viewed in existing data mining techniques. With the rapid development of database technology, many data storage increases, and data mining technology has become more and more important and expanded to various fields in recent years. Association rule mining is the most active research technique of data mining. Data mining technology is used for potentially useful information extraction and knowledge from big data sets. The results demonstrate that the precision ratio of the presented technique is high comparable to other existing techniques with the same recall rate, i.e., the R-tree algorithm. The proposed technique by the mining effectively controls the noise data, and the precision rate is also kept very high, which indicates the highest accuracy of the technique. This article makes a systematic and detailed analysis of data mining technology by using the Apriori algorithm.
format	article
author	Zhao Zhenyi Jian Zhou Gaba Gurjot Singh Alroobaea Roobaea Masud Mehedi Rubaiee Saeed
author_facet	Zhao Zhenyi Jian Zhou Gaba Gurjot Singh Alroobaea Roobaea Masud Mehedi Rubaiee Saeed
author_sort	Zhao Zhenyi
title	An improved association rule mining algorithm for large data
title_short	An improved association rule mining algorithm for large data
title_full	An improved association rule mining algorithm for large data
title_fullStr	An improved association rule mining algorithm for large data
title_full_unstemmed	An improved association rule mining algorithm for large data
title_sort	improved association rule mining algorithm for large data
publisher	De Gruyter
publishDate	2021
url	https://doaj.org/article/f1baa2b003d14ef78577a93207b8a422
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_version_	1718371655665844224

An improved association rule mining algorithm for large data

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