| dc.creator | Michelakos, I. | en |
| dc.creator | Mallios, N. | en |
| dc.creator | Papageorgiou, E. | en |
| dc.creator | Vassilakopoulos, M. | en |
| dc.date.accessioned | 2015-11-23T10:39:36Z | |
| dc.date.available | 2015-11-23T10:39:36Z | |
| dc.date.issued | 2010 | |
| dc.identifier | 10.1109/3PGCIC.2010.47 | |
| dc.identifier.isbn | 9780769542379 | |
| dc.identifier.uri | http://hdl.handle.net/11615/31005 | |
| dc.description.abstract | The Ant Colony Optimization (ACO) technique was inspired by the ants' behaviour throughout their exploration for food. The use of this technique has been very successful for several problems. Besides, Data Mining (DM) has emerged as an important technology with numerous practical applications, due to the wide availability of a vast amount of data. The collaborative use of ACO and DM is very promising. In this paper, we review ACO, DM, Classification and Clustering (popular DM tasks) and focus on the use of ACO for Classification and Clustering. Moreover, we briefly present related applications and examples and outline possible future trends of this promising collaborative use of techniques. © 2010 IEEE. | en |
| dc.source.uri | http://www.scopus.com/inward/record.url?eid=2-s2.0-84873170816&partnerID=40&md5=c4d53bb8bdb94d3687029f889ef97842 | |
| dc.subject | Ant Colony Optimization (ACO) | en |
| dc.subject | Classification | en |
| dc.subject | Clustering | en |
| dc.subject | Data Mining | en |
| dc.subject | Classification and clustering | en |
| dc.subject | Possible futures | en |
| dc.subject | Algorithms | en |
| dc.subject | Ant colony optimization | en |
| dc.subject | Classification (of information) | en |
| dc.subject | Distributed computer systems | en |
| dc.subject | Internet | en |
| dc.subject | Artificial intelligence | en |
| dc.title | Ant colony optimization and data mining: Techniques and trends | en |
| dc.type | conferenceItem | en |
