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|3 10.33948/0584-023-001-001
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|a eng
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044 |
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|b السعودية
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100 |
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|9 523837
|a Ykhlef, Mourad
|e Author
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245 |
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|a A Quantum Swarm Evolutionary Algorithm For Mining Association Rules In Large Databases
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260 |
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|b جامعة الملك سعود
|c 2011
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300 |
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|a 1 - 6
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336 |
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|a بحوث ومقالات
|b Article
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520 |
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|b Association rule mining aims to extract the correlation or causal structure existing between a set of frequent items or attributes in a database. These associations are represented by mean of rules. Association rule mining methods provide a robust but non-linear approach to find associations. The search for association rules is an NP -complete problem. The complexities mainly arise in exploiting huge number of database transactions and items. In this article we propose a new algorithm to extract the best rules in a reasonable time of execution but without assuring always the optimal solutions. The new derived algorithm is based on Quantum Swarm Evolutionary approach; it gives better results compared to genetic algorithms.
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653 |
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|a تكنولوجيا المعلومات
|a قواعد البيانات
|a الخوارزميات الجينية
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692 |
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|b Quantum Evolutionary Algorithm
|b Swarm Intelligence
|b Association Rule Mining
|b Fitness
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773 |
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|c 001
|e Journal of King Saud University (Computer and Information Sciences)
|f Maǧalaẗ ǧamʼaẗ al-malīk Saud : ùlm al-ḥasib wa al-maʼlumat
|l 001
|m مج23, ع1
|o 0584
|s مجلة جامعة الملك سعود - علوم الحاسب والمعلومات
|v 023
|x 1319-1578
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856 |
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|u 0584-023-001-001.pdf
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930 |
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|d y
|p y
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|a science
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999 |
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|c 971934
|d 971934
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