Name
Abstract | ||
|---|---|---|
In this paper, we introduce a new method to solve the unsupervised clustering problem, based on a modelling of the chemical recognition system of ants. This system allow ants to discriminate between nestmates and intruders, and thus to create homogeneous groups of individuals sharing a similar odor by continuously exchanging chemical cues. This phenomenon, known as "colonial closure", inspired us into developing a new clustering algorithm and then comparing it to a well-known method such as... |
Year | Venue | Field |
|---|---|---|
2002 | ECAI | Data mining,CURE data clustering algorithm,Computer science,Artificial intelligence,FLAME clustering,Cluster analysis,Canopy clustering algorithm,Correlation clustering,Recognition system,Affinity propagation,Pattern recognition,Hierarchical clustering of networks,Machine learning |
DocType | Citations | PageRank |
Conference | 3 | 0.47 |
References | Authors | |
1 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nicolas Labroche | 1 | 139 | 17.87 |
| Nicolas Monmarché | 2 | 305 | 32.73 |
| Gilles Venturini | 3 | 660 | 82.45 |