Mining association rule from large databases.
Association rules, introduced by Agrawal, Imielinski and Swami, is one of data mining technique to discover interesting rules or relationships among attributes in databases. It has attracted great attention in database research communities in recent years. In this paper, we propose a Mining Associat...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Penerbit UTM Press
2001
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| Online Access: | http://eprints.utm.my/8764/1/MohdNoorMdSap2001_MiningAssociationRuleFromLarge.PDF |
| _version_ | 1796854452263583744 |
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| author | Defit, Sarjon Md. Sap, Mohd. Noor |
| author_facet | Defit, Sarjon Md. Sap, Mohd. Noor |
| author_sort | Defit, Sarjon |
| collection | ePrints |
| description | Association rules, introduced by Agrawal, Imielinski and Swami, is one of data mining technique to discover interesting rules or relationships among attributes in databases. It has attracted great attention in database research communities in recent years. In this paper, we propose a Mining Association Rules (MAR) model which integrate intelligent and data analysis techniques. MAR model has been implemented and tested using Jakarta Stock Exchange (JSA) databases. Our study conclude that MAR model can improve the performance ability of generated rules. In this paper, we explain the proposed MAR model, testing and experimental results in looking into the performance of the model and conclusion. |
| first_indexed | 2024-03-05T18:14:17Z |
| format | Article |
| id | utm.eprints-8764 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T18:14:17Z |
| publishDate | 2001 |
| publisher | Penerbit UTM Press |
| record_format | dspace |
| spelling | utm.eprints-87642017-11-01T04:17:46Z http://eprints.utm.my/8764/ Mining association rule from large databases. Defit, Sarjon Md. Sap, Mohd. Noor QA75 Electronic computers. Computer science Association rules, introduced by Agrawal, Imielinski and Swami, is one of data mining technique to discover interesting rules or relationships among attributes in databases. It has attracted great attention in database research communities in recent years. In this paper, we propose a Mining Association Rules (MAR) model which integrate intelligent and data analysis techniques. MAR model has been implemented and tested using Jakarta Stock Exchange (JSA) databases. Our study conclude that MAR model can improve the performance ability of generated rules. In this paper, we explain the proposed MAR model, testing and experimental results in looking into the performance of the model and conclusion. Penerbit UTM Press 2001-12 Article PeerReviewed application/pdf en http://eprints.utm.my/8764/1/MohdNoorMdSap2001_MiningAssociationRuleFromLarge.PDF Defit, Sarjon and Md. Sap, Mohd. Noor (2001) Mining association rule from large databases. Jurnal Teknologi Maklumat, 13 (2). pp. 16-37. ISSN 0128-3790 |
| spellingShingle | QA75 Electronic computers. Computer science Defit, Sarjon Md. Sap, Mohd. Noor Mining association rule from large databases. |
| title | Mining association rule from large databases. |
| title_full | Mining association rule from large databases. |
| title_fullStr | Mining association rule from large databases. |
| title_full_unstemmed | Mining association rule from large databases. |
| title_short | Mining association rule from large databases. |
| title_sort | mining association rule from large databases |
| topic | QA75 Electronic computers. Computer science |
| url | http://eprints.utm.my/8764/1/MohdNoorMdSap2001_MiningAssociationRuleFromLarge.PDF |
| work_keys_str_mv | AT defitsarjon miningassociationrulefromlargedatabases AT mdsapmohdnoor miningassociationrulefromlargedatabases |