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CNAR-M: A model for mining critical negative association rules

Association rules mining has been extensively studied in various multidiscipline applications. One of the important categories in association rule is known as Negative Association Rule (NAR). Significant NAR is very useful in certain domain applications; however it is hardly to be captured and discr...

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Main Authors: Herawan, Tutut, Zailani, Abdullah
Format: Conference or Workshop Item
Language:English
Published: Springer, Berlin, Heidelberg 2012
Subjects:
QA76 Computer software
Online Access:http://umpir.ump.edu.my/id/eprint/27009/1/CNAR-M-%20A%20model%20for%20mining%20critical%20negative%20association%20rules.pdf
http://umpir.ump.edu.my/id/eprint/27009/
https://doi.org/10.1007/978-3-642-34289-9_20
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spelling my.ump.umpir.270092020-03-23T02:32:52Z http://umpir.ump.edu.my/id/eprint/27009/ CNAR-M: A model for mining critical negative association rules Herawan, Tutut Zailani, Abdullah QA76 Computer software Association rules mining has been extensively studied in various multidiscipline applications. One of the important categories in association rule is known as Negative Association Rule (NAR). Significant NAR is very useful in certain domain applications; however it is hardly to be captured and discriminated. Therefore, in this paper we proposed a model called Critical Negative Association Rule Model (CNAR-M) to extract the Critical Negative Association Rule (CNAR) with higher Critical Relative Support (CRS) values. The result shows that the CNAR-M can mine CNAR from the benchmarked and real datasets. Moreover, it also can discriminate the CNAR with others association rules. Springer, Berlin, Heidelberg 2012 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/27009/1/CNAR-M-%20A%20model%20for%20mining%20critical%20negative%20association%20rules.pdf Herawan, Tutut and Zailani, Abdullah (2012) CNAR-M: A model for mining critical negative association rules. In: 6th International Symposium on Intelligence Computation and Applications (ISICA 2012), 27-28 October 2012 , Wuhan, China. pp. 170-179., 316. ISBN 978-3-642-34289-9 https://doi.org/10.1007/978-3-642-34289-9_20
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA76 Computer software
spellingShingle QA76 Computer software
Herawan, Tutut
Zailani, Abdullah
CNAR-M: A model for mining critical negative association rules
description Association rules mining has been extensively studied in various multidiscipline applications. One of the important categories in association rule is known as Negative Association Rule (NAR). Significant NAR is very useful in certain domain applications; however it is hardly to be captured and discriminated. Therefore, in this paper we proposed a model called Critical Negative Association Rule Model (CNAR-M) to extract the Critical Negative Association Rule (CNAR) with higher Critical Relative Support (CRS) values. The result shows that the CNAR-M can mine CNAR from the benchmarked and real datasets. Moreover, it also can discriminate the CNAR with others association rules.
format Conference or Workshop Item
author Herawan, Tutut
Zailani, Abdullah
author_facet Herawan, Tutut
Zailani, Abdullah
author_sort Herawan, Tutut
title CNAR-M: A model for mining critical negative association rules
title_short CNAR-M: A model for mining critical negative association rules
title_full CNAR-M: A model for mining critical negative association rules
title_fullStr CNAR-M: A model for mining critical negative association rules
title_full_unstemmed CNAR-M: A model for mining critical negative association rules
title_sort cnar-m: a model for mining critical negative association rules
publisher Springer, Berlin, Heidelberg
publishDate 2012
url http://umpir.ump.edu.my/id/eprint/27009/1/CNAR-M-%20A%20model%20for%20mining%20critical%20negative%20association%20rules.pdf
http://umpir.ump.edu.my/id/eprint/27009/
https://doi.org/10.1007/978-3-642-34289-9_20
_version_ 1662754753568833536
score 13.211869

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