Combines the Apriori and FCM Algorithm to Improve the Extracted Association Rules with Determine the Minimum Support Automatically
Apriori algorithm is the most popular algorithm in association rules mining. One of the problems the Apriori algorithm is that the user must specify a minimum support threshold. Consider that a user wants to implement the Apriori algorithm on a database with millions of transactions; Users will not...
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| Format: | Article |
| Language: | English |
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University of Tehran
2015-06-01
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| Series: | Journal of Information Technology Management |
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| Online Access: | https://jitm.ut.ac.ir/article_53863_6241bdcb2065f67d71456b81c7738de3.pdf |
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| _version_ | 1850195391896616960 |
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| author | Heydar Jafarzadeh Chamran Asgari Amir Amiry |
| author_facet | Heydar Jafarzadeh Chamran Asgari Amir Amiry |
| author_sort | Heydar Jafarzadeh |
| collection | DOAJ |
| description | Apriori algorithm is the most popular algorithm in association rules mining. One of the problems the Apriori algorithm is that the user must specify a minimum support threshold. Consider that a user wants to implement the Apriori algorithm on a database with millions of transactions; Users will not have the necessary knowledge about all the transactions in the database and therefore cannot determine an appropriate threshold. The aim of this paper is improved the Apriori algorithm to automatically determine the minimum support. To achieve this, we will try to use fuzzy logic before of using the Apriori algorithm on data contained in the database, put the data in different clusters and try the offer to user the most appropriate threshold automatically. We hope this will be any rule that may be of interest not lost, because of inappropriate threshold specified by the user and also not extracted any rule useless |
| format | Article |
| id | doaj-art-0fd01f77f69e412aa34c297ceed3bd20 |
| institution | OA Journals |
| issn | 2008-5893 2423-5059 |
| language | English |
| publishDate | 2015-06-01 |
| publisher | University of Tehran |
| record_format | Article |
| series | Journal of Information Technology Management |
| spelling | doaj-art-0fd01f77f69e412aa34c297ceed3bd202025-08-20T02:13:45ZengUniversity of TehranJournal of Information Technology Management2008-58932423-50592015-06-017225928210.22059/jitm.2015.5386353863Combines the Apriori and FCM Algorithm to Improve the Extracted Association Rules with Determine the Minimum Support AutomaticallyHeydar Jafarzadeh0Chamran Asgari1Amir Amiry2MSc., Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Ilam, IranMSc., Department of Computer Engineering, Payame Noor University, IranMSc., Department of Computer Engineering, Islamic Azad University, Malayer, IranApriori algorithm is the most popular algorithm in association rules mining. One of the problems the Apriori algorithm is that the user must specify a minimum support threshold. Consider that a user wants to implement the Apriori algorithm on a database with millions of transactions; Users will not have the necessary knowledge about all the transactions in the database and therefore cannot determine an appropriate threshold. The aim of this paper is improved the Apriori algorithm to automatically determine the minimum support. To achieve this, we will try to use fuzzy logic before of using the Apriori algorithm on data contained in the database, put the data in different clusters and try the offer to user the most appropriate threshold automatically. We hope this will be any rule that may be of interest not lost, because of inappropriate threshold specified by the user and also not extracted any rule uselesshttps://jitm.ut.ac.ir/article_53863_6241bdcb2065f67d71456b81c7738de3.pdf"Apriori Algorithm""Association Rules""Fuzzy Clustering""Support" |
| spellingShingle | Heydar Jafarzadeh Chamran Asgari Amir Amiry Combines the Apriori and FCM Algorithm to Improve the Extracted Association Rules with Determine the Minimum Support Automatically Journal of Information Technology Management "Apriori Algorithm" "Association Rules" "Fuzzy Clustering" "Support" |
| title | Combines the Apriori and FCM Algorithm to Improve the Extracted Association Rules with Determine the Minimum Support Automatically |
| title_full | Combines the Apriori and FCM Algorithm to Improve the Extracted Association Rules with Determine the Minimum Support Automatically |
| title_fullStr | Combines the Apriori and FCM Algorithm to Improve the Extracted Association Rules with Determine the Minimum Support Automatically |
| title_full_unstemmed | Combines the Apriori and FCM Algorithm to Improve the Extracted Association Rules with Determine the Minimum Support Automatically |
| title_short | Combines the Apriori and FCM Algorithm to Improve the Extracted Association Rules with Determine the Minimum Support Automatically |
| title_sort | combines the apriori and fcm algorithm to improve the extracted association rules with determine the minimum support automatically |
| topic | "Apriori Algorithm" "Association Rules" "Fuzzy Clustering" "Support" |
| url | https://jitm.ut.ac.ir/article_53863_6241bdcb2065f67d71456b81c7738de3.pdf |
| work_keys_str_mv | AT heydarjafarzadeh combinestheaprioriandfcmalgorithmtoimprovetheextractedassociationruleswithdeterminetheminimumsupportautomatically AT chamranasgari combinestheaprioriandfcmalgorithmtoimprovetheextractedassociationruleswithdeterminetheminimumsupportautomatically AT amiramiry combinestheaprioriandfcmalgorithmtoimprovetheextractedassociationruleswithdeterminetheminimumsupportautomatically |