Title :
Wise mining method through ant colony optimization
Author :
Jianxiong, Yang ; Watada, Junzo
Author_Institution :
Grad. Sch. of Inf., Waseda Univ., Kitakyushu, Japan
Abstract :
This paper proposes an algorithm for data mining named Pheromone-Miner (ant-colony-based data miner). The algorithm is inspired by both researches on the behavior of real ant colonies and data mining concepts as well as principles. The goal of Pheromone-Miner is to extract more exact knowledge from a database. Pheromone-based mining breaks through limitations of other mining approaches. We compare the performance of pheromone-miner with a general semantic miner. The accident causes discovered by ant-miner are considerably more accurate than those discovered by a general semantic miner. In a word, this evolutionary algorithm is suitable for improving the accuracy of data miners.
Keywords :
data mining; optimisation; Pheromone-Miner; ant colony optimization; ant-colony-based data miner; data mining; evolutionary algorithm; general semantic miner; knowledge extraction; wise mining method; Ant colony optimization; Clustering algorithms; Cybernetics; Data mining; Databases; Electronic mail; Insects; Production systems; Robustness; USA Councils; ant colony optimization algorithm; data mining; knowledge discovery; pheromone;
Conference_Titel :
Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-2793-2
Electronic_ISBN :
1062-922X
DOI :
10.1109/ICSMC.2009.5346807