Association Rule Mining using a Bacterial Colony Algorithm

被引：0
作者：
da Cunha, Danilo S. [1 ]
Xavier, Rafael S. [1 ]
Ferrari, Daniel G. [1 ]
de Castro, Leandro N. [1 ]
机构：
[1] Univ Prebiteriana Mackenzie, Nat Comp Lab LCoN, Sao Paulo, Brazil
来源：
2015 LATIN AMERICA CONGRESS ON COMPUTATIONAL INTELLIGENCE (LA-CCI) | 2015年
关键词：
bio-inspired algorithm; bacterial colony; association rules; data mining; OPTIMIZATION; FOUNDATIONS;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Bacterial colonies perform a cooperative distributed exploration of the environment. This paper describes bacterial colony networks and their skills to explore resources as a tool for mining association rules in databases. The proposed algorithm is designed to maintain diverse solutions to the problem at hand, and its performance is compared to other well-known bio-inspired algorithms, including a genetic and an immune algorithm (CLONALG) and, also, to Apriori over some benchmarks from the literature.
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页数：6
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