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.
Original language | English |
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Title of host publication | Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics |
Pages | 1833-1839 |
Number of pages | 7 |
DOIs | |
Publication status | Published - 2009 |
Event | 2009 IEEE International Conference on Systems, Man and Cybernetics, SMC 2009 - San Antonio, TX Duration: 2009 Oct 11 → 2009 Oct 14 |
Other
Other | 2009 IEEE International Conference on Systems, Man and Cybernetics, SMC 2009 |
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City | San Antonio, TX |
Period | 09/10/11 → 09/10/14 |
Keywords
- Ant colony optimization algorithm
- Data mining
- Knowledge discovery
- Pheromone
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Human-Computer Interaction