A Novel PSO based Approach for Mining Association Rules
Автор:Jitendra Agrawal,Shikha Agrawal and Ankita singhai Год: 2013 Издание:LAP Lambert Academic Publishing Страниц: 76 ISBN: 9783659468506 Association rule mining is the most popular data mining techniques to find association among items in a set by mining necessary patterns in a large database, frequently used in marketing, advertising and inventory control. Typically association rules consider only items enumerated in transactions, referred as positive association rules but not consider negative occurrence of attributes that are also useful in market-basket analysis to identify products that conflict with each other or products that complement each other. Also for mining those positive rules that qualify the user specified threshold criteria, algorithm generates too many candidate itemsets by scanning database multiple times. In order to resolve all the bottleneck of association rule mining algorithm, in this we propose an algorithm SARIC which implements Set Particle Swarm Optimization heuristic technique for generating association rules from a database that also consider negative occurrence of attribute along with...
