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 |
|---|---|
| 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 |
|---|---|
| City | San Antonio, TX |
| Period | 09/10/11 → 09/10/14 |
Fingerprint
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
Cite this
Wise mining method through ant colony optimization. / Jianxiong, Yang; Watada, Junzo.
Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. 2009. p. 1833-1839 5346807.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Wise mining method through ant colony optimization
AU - Jianxiong, Yang
AU - Watada, Junzo
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
KW - Ant colony optimization algorithm
KW - Data mining
KW - Knowledge discovery
KW - Pheromone
UR - http://www.scopus.com/inward/record.url?scp=74849117644&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=74849117644&partnerID=8YFLogxK
U2 - 10.1109/ICSMC.2009.5346807
DO - 10.1109/ICSMC.2009.5346807
M3 - Conference contribution
AN - SCOPUS:74849117644
SN - 9781424427949
SP - 1833
EP - 1839
BT - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ER -