کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
483912 | 702880 | 2011 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A Quantum Swarm Evolutionary Algorithm for mining association rules in large databases
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of King Saud University - Computer and Information Sciences - Volume 23, Issue 1, January 2011, Pages 1–6
Journal: Journal of King Saud University - Computer and Information Sciences - Volume 23, Issue 1, January 2011, Pages 1–6
نویسندگان
Mourad Ykhlef,