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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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Tehran
2015-06-01
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| Series: | Journal of Information Technology Management |
| Subjects: | |
| Online Access: | https://jitm.ut.ac.ir/article_53863_6241bdcb2065f67d71456b81c7738de3.pdf |
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| Summary: | 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 |
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| ISSN: | 2008-5893 2423-5059 |