>
Fa   |   Ar   |   En
   A Quantum Swarm Evolutionary Algorithm for mining association rules in large databases  
   
نویسنده Ykhlef Mourad
منبع journal of king saud university - computer and information sciences - 2011 - دوره : 23 - شماره : 1 - صفحه:1 -6
چکیده    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.
کلیدواژه Quantum EvolutionaryAlgorithm;Swarm intelligence;Association rule mining;Fitness
آدرس King Saud University, College of Computer and Information Sciences, Saudi Arabia
پست الکترونیکی ykhlef@ksu.edu.sa
 
     
   
Authors
  
 
 

Copyright 2023
Islamic World Science Citation Center
All Rights Reserved